I’ve been following emerging treatments for Alzheimer’s disease since I founded my NGO in Poland seven years ago. A lot has happened since then: the rise of blood-based biomarkers, growing challenges to the amyloid hypothesis as a complete explanation of the disease, the approval of the first two disease-modifying anti-amyloid antibodies, major advances in tau-targeted therapeutics, growing recognition of neuroinflammation and the gut–brain axis as therapeutic targets, breakthroughs in understanding the brain’s glymphatic and meningeal lymphatic systems, and the emergence of entirely new approaches—from focused ultrasound to experimental surgery aimed at restoring the brain’s natural waste-clearance mechanisms.

However, a sugery for Alzheimer’s disease never even crossed my mind.

On October 20, 2026, surgeons at the Provincial Specialist Hospital in Słupsk, Poland, performed an unusual operation on a 58-year-old man with early-stage Alzheimer’s disease. They did not open his skull, implant electrodes into his brain, or administer an experimental drug. Instead, they operated on the lymphatic system in his neck.

Over nearly five hours, the surgical team, led by Dr. Daniel Maliszewski, created two connections between cervical lymph nodes and nearby veins, using the Symani robotic microsurgical system. Three additional lymphatic–venous connections were constructed in the lower limbs.

Two days later, the patient was discharged without reported postoperative complications. He also described sleeping better than he had in a long time.

But the most important question remains unanswered: Could improving lymphatic drainage from the brain actually slow Alzheimer’s disease?

The answer could open an entirely new therapeutic direction in neurodegeneration.

Alzheimer’s disease: From targeting proteins to targeting their clearance

Alzheimer’s disease is characterized by several interconnected pathological processes:

• Amyloid-β (Aβ) accumulation: Extracellular amyloid plaques are among the earliest detectable pathological features of Alzheimer’s disease.

• Tau pathology: Hyperphosphorylated tau aggregates into intracellular neurofibrillary tangles, which are strongly associated with neuronal dysfunction and cognitive deterioration.

• Neuroinflammation: Activated microglia and astrocytes contribute to chronic inflammation and potentially exacerbate neurodegeneration.

• Synaptic dysfunction and neuronal loss: Progressive disruption of neural circuits ultimately drives cognitive impairment.

For decades, drug development has largely focused on inhibiting the production or aggregation of pathological proteins, or removing them once accumulated. Over the past decade, the amyloid hypothesis—the dominant theory that amyloid-β accumulation drives Alzheimer’s disease—has faced growing challenges. Particularly compelling evidence comes from Dr Yakeel Quiroz’s research on families with hereditary Alzheimer’s disease in Colombia. In a landmark 2019 Nature Medicine study, her team identified a woman carrying the highly penetrant PSEN1 E280A mutation who remained cognitively intact for nearly 30 years beyond her expected age of disease onset, despite extraordinarily high levels of amyloid plaques. Remarkably, she had relatively little tau pathology and carried a protective APOE3 Christchurch variant. In 2023, researchers identified another exceptionally resilient individual carrying the same Alzheimer’s-causing mutation and a rare RELN-COLBOS variant, who remained cognitively intact until age 67 despite extensive amyloid accumulation and relatively limited tau pathology in key brain regions. These findings challenge the notion that amyloid accumulation alone is sufficient to cause dementia and suggest that tau pathology and its anatomical spread may be more closely linked to cognitive decline. They support a more nuanced model in which amyloid may initiate disease processes, while tau pathology is more closely associated with neurodegeneration and clinical symptoms.

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The brain has its own waste-clearance system

In 2012, researchers led by Maiken Nedergaard described a brain-wide pathway through which cerebrospinal fluid exchanges with interstitial fluid, facilitating the movement of metabolic waste, including amyloid-β.

This pathway became known as the glymphatic system, reflecting the involvement of glial cells in a lymphatic-like clearance process.

A few years later, researchers identified functional lymphatic vessels in the meninges—the membranes surrounding the brain.

These vessels provide an important connection between the central nervous system and peripheral lymphatic circulation.

The simplified drainage pathway is:

Brain interstitial fluid → cerebrospinal fluid exchange → meningeal lymphatic vessels → deep cervical lymph nodes → systemic lymphatic and venous circulation.

Studies suggest that the efficiency of these clearance pathways may deteriorate with aging and neurodegenerative disease.

Importantly, the glymphatic system is also linked to sleep physiology. Experimental evidence suggests that sleep influences cerebrospinal fluid dynamics and the clearance of metabolic substances from the brain.

This is particularly relevant because sleep disturbances and Alzheimer’s pathology appear to interact bidirectionally.

However, the precise contribution of glymphatic dysfunction to human Alzheimer’s disease—and whether correcting it changes disease progression—remains under investigation.

A surgical shortcut for brain waste removal

The experimental procedure is called deep cervical lymphatic–venous anastomosis (dcLVA).

An anastomosis is a surgically created connection between two anatomical structures.

Lymphatic–venous anastomoses are not themselves new. Microsurgeons have used similar techniques for years to treat conditions such as lymphedema, where impaired lymphatic drainage causes fluid accumulation.

The novelty lies in applying the principle to neurodegenerative disease.

During dcLVA, surgeons connect deep cervical lymphatic structures to nearby veins, theoretically providing an additional route for lymphatic outflow.

The proposed mechanism is straightforward:

1. Alzheimer’s disease may be associated with impaired drainage of interstitial and cerebrospinal fluid.

2. Reduced clearance could contribute to the accumulation of amyloid-β, tau and inflammatory mediators.

3. Surgically creating additional lymphatic–venous connections might decrease resistance to outflow.

4. Improved drainage could potentially enhance the removal of pathological substances.

5. Over time, this might reduce neuroinflammation, preserve neuronal function and slow cognitive decline.

The procedure does not directly remove amyloid plaques or tau tangles from the brain. Rather, it attempts to modify the physiological environment responsible for clearing soluble substances.

There is, however, a crucial unresolved assumption: that cervical lymphatic outflow is a meaningful bottleneck in cerebral waste clearance.

If the primary limitation lies upstream—in impaired interstitial transport, altered cerebrospinal fluid dynamics or degeneration of meningeal lymphatics—creating an additional connection in the neck may have limited benefit.

What have clinical studies shown so far?

Although the Słupsk procedure was the first reported operation of its kind in Poland, Chinese teams began exploring cervical lymphatic surgery for Alzheimer’s several years earlier.

By 2026, several clinical reports had appeared, including larger prospective cohorts.

Study 1: 139 patients with severe Alzheimer’s disease

In February 2026, Fu et al (2026) published a prospective, single-arm study in Alzheimer’s & Dementia involving 139 patients with severe Alzheimer’s disease.

Patients underwent dcLVA and were monitored for up to six months.

The investigators reported:

• An average improvement of 1.6 points on the Mini-Mental State Examination (MMSE) 48 hours after surgery.

• An average MMSE improvement of 1.28 points at six months.

• Improvements in reported daily functioning, neuropsychiatric symptoms and sleep.

• Changes in Alzheimer’s-related cerebrospinal fluid and plasma biomarkers, including Aβ and phosphorylated tau.

The biomarker findings were particularly intriguing. In a prospective Chinese study involving 139 patients with severe Alzheimer’s disease, researchers observed significant reductions in cerebrospinal fluid (CSF) concentrations of Aβ42 (−176.2, p < 0.001), Aβ40 (−7,706.7, p < 0.001), and phosphorylated tau181 (−37.0, p = 0.004) just 48 hours after surgery. Meanwhile, plasma Aβ40 (+50.3, p = 0.013) and p-tau217 (+3.73, p < 0.001) increased, suggesting a possible redistribution of Alzheimer’s-associated proteins from the central nervous system into the circulation. At six months, plasma Aβ40 and Aβ42 remained significantly elevated, while p-tau217 had fallen below baseline. These results are consistent with the proposed brain-clearance mechanism.

However, the findings need cautious interpretation.

The study had no randomized control group, and only 95 patients completed the six-month cognitive assessment. Moreover, changes in cognitive scores did not consistently correlate with changes in biomarkers.

Most importantly, an improvement of approximately one MMSE point cannot independently establish meaningful reversal of neurodegeneration, particularly in patients with advanced dementia.

In a separate publication, they report “daily living” changes post-op:
t six months, they reported:

• Daily functioning (ADL): Significant improvement in activities such as dressing and performing simple household tasks (reported score change −59.5; p < 0.001).

• Neuropsychiatric symptoms (NPI): A 9.9-point reduction (p < 0.001), suggesting improvements in behavioral and psychological symptoms.

• Caregiver distress (NPI-D): A 3.4-point reduction (p < 0.001).

• Sleep (SDI): Significant improvements at one, three, and six months.

• Speech and social interaction: Follow-up videos showed patients speaking more spontaneously, responding faster, recognizing family members more clearly, and engaging more socially.

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A major regulatory warning

Despite growing clinical interest, China’s National Health Commission prohibited the clinical application of deep cervical lymphatic–venous anastomosis for Alzheimer’s disease in July 2025.

The decision reflected concerns about insufficient evidence supporting efficacy and safety, as well as the premature clinical adoption of the technique.

Important mechanistic questions remain unresolved, including:

• Are the surgically created connections consistently patent over time?

• What are the actual pressure gradients between the lymphatic and venous systems?

• Could venous reflux compromise drainage?

• Does the operation measurably increase clearance from brain tissue itself?

• Do biomarker changes translate into long-term preservation of cognition?

I do wonder to what extent it was prohibited so that the unaccredited, wannabe longevity medicine centers (that have nothing to do with real longevity medicine) don’t start mass offering it for “improved brain clearning”. If you want to understand the real longevity medicine, see Longevity Education Hub

What would convince us that it works?

In my view, demonstrating a patent connection between a cervical lymphatic structure and a vein is only the beginning.

A convincing proof of mechanism would require showing that this peripheral surgical intervention actually improves cerebral clearance.

Ideally, future trials would combine several complementary measurements:

1. Direct or indirect physiological measurements

Quantify changes in lymphatic flow, anastomotic patency, venous reflux and cerebrospinal fluid clearance dynamics.

2. Molecular biomarkers

Monitor plasma and cerebrospinal fluid Aβ42/40, p-tau217, p-tau181, neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP).

These could help distinguish changes in amyloid pathology, tau pathology, neuronal injury and astroglial activation.

3. Molecular imaging

Use amyloid and tau PET to determine whether the intervention changes cerebral pathological burden over time.

4. Clinical outcomes

Measure cognitive trajectories using validated instruments such as CDR-SB and ADAS-Cog, alongside daily functioning, caregiver-reported outcomes and quality of life.

5. Appropriate control groups

Randomized controlled trials are essential to distinguish surgery-associated effects from placebo responses, changes in postoperative care, measurement variability and other confounding factors.

The planned Polish follow-up includes cognitive testing, blood biomarkers, sleep measurements and MRI-based assessment of clearance physiology.

The team has authorization for 15 experimental procedures, with the first patient expected to be followed for at least two years.

Meanwhile, controlled trials such as CLEAN-AD are being developed to evaluate cervical lymphatic–venous surgery more systematically.

How does this compare with existing Alzheimer’s therapies?

To appreciate why an entirely different approach is attracting attention, it is useful to understand what current treatments can—and cannot—achieve.

Historically, most approved Alzheimer’s medications have focused on managing symptoms rather than altering the underlying disease.

That changed with the arrival of anti-amyloid monoclonal antibodies.

Disease-modifying therapies: Anti-amyloid antibodies

The introduction of monoclonal antibodies targeting amyloid-β represented an important shift from symptom management toward treatment of underlying pathology.

Two leading approved therapies are lecanemab and donanemab.

These percentages are relative reductions in decline on different clinical scales and populations. They should not be interpreted as a direct head-to-head comparison.

Lecanemab

In the Phase 3 CLARITY AD study involving 1,795 participants with early Alzheimer’s disease, lecanemab significantly slowed clinical decline compared with placebo over 18 months.

The trial reported a 27% reduction in decline measured using the Clinical Dementia Rating–Sum of Boxes (CDR-SB).

This was an important demonstration that directly targeting amyloid pathology could produce a measurable clinical benefit.

In 2026, the FDA also approved a subcutaneous starting regimen, allowing suitable patients to administer lecanemab at home rather than relying exclusively on intravenous infusion facilities.

Donanemab

In the Phase 3 TRAILBLAZER-ALZ 2 study, donanemab slowed clinical decline by approximately 35% on the integrated Alzheimer’s Disease Rating Scale among participants with low-to-medium tau pathology.

Across the broader combined trial population, slowing on that measure was approximately 22%.

Donanemab demonstrated substantial amyloid plaque reduction, and treatment protocols permit discontinuation after amyloid clearance reaches predefined thresholds

These treatments are important advances, but they have several limitations.

First, they slow rather than reverse cognitive deterioration.

Second, their pivotal efficacy evidence comes primarily from patients with mild cognitive impairment or mild dementia due to Alzheimer’s disease.

This necessitates patient selection, MRI surveillance and careful consideration of risk factors such as APOE ε4 genotype.

Finally, amyloid removal addresses only one component of Alzheimer’s pathophysiology. Tau pathology, neuroinflammation, mitochondrial dysfunction, vascular abnormalities and synaptic degeneration remain highly relevant therapeutic targets.

Active Phase 2/3 trials for AD

Beyond the recently approved anti-amyloid antibodies, the Alzheimer’s therapeutic pipeline is becoming increasingly diverse, with clinical trials targeting tau pathology, neuroinflammation, synaptic dysfunction, and blood–brain barrier delivery. Among the most promising is diranersen (BIIB080), an antisense oligonucleotide targeting tau production, which demonstrated substantial reductions in CSF tau and encouraging cognitive outcomes in Phase 2, although its primary endpoint was not met (dose-response relationship in CDR-SB). Other innovative approaches include sargramostim, which modulates innate immunity; trontinemab, Roche’s next-generation anti-amyloid antibody engineered to cross the blood–brain barrier more efficiently; AADvac1, an active tau vaccine being investigated in combination with donanemab; and zervimesine, an oral small molecule designed to protect synapses from toxic amyloid oligomers. However, the field continues to face significant translational challenges. Most notably, Novo Nordisk’s large Phase 3 EVOKE and EVOKE+ trials failed to demonstrate that semaglutide slows cognitive decline, despite strong preclinical and epidemiological rationale.

A new direction for neurodegenerative medicine?

When I first became involved in the Alzheimer’s field seven years ago, the disease was still largely surrounded by silence and stigma, and there was nothing anyone could do about the disease (to an extent that would significantly delay the onset/ammeliorate daily life to a great extent). People rarely talked about it, and many never received a diagnosis. In some ways, that reluctance was understandable: why would someone want to know they were developing an incurable disease when there was so little medicine could offer? Seven years later, the landscape looks remarkably different. An d7 years is really not that long from a pharma perspective! We now have blood-based biomarkers, the first disease-modifying therapies, and an increasingly diverse pipeline of approaches that would have seemed almost unimaginable back then. Early diagnosis is becoming genuinely actionable, even if our therapeutic options remain far from sufficient. To me, this fundamentally changes the conversation around Alzheimer’s: knowing one’s risk or diagnosis is no longer just about preparing for an inevitable decline, but increasingly about having an opportunity to intervene. Of course, the decision to know or not to know must remain the individual’s choice, particularly when it comes to genetic risk. But that choice carries a different meaning when something can actually be done. Looking at how much has changed in just seven years, I find it difficult not to be excited about what the next seven might bring. For the first time since I entered this field, optimism about the future of Alzheimer’s treatment feels grounded in more than hope

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Four years of signals at ARDD

ARDD has a long history of announcements that indicated that big pharma is getting serious about longevity

ARDD 2023 — the strategic discussion begins. Lilly’s Benjamin Yaden and Novo’s Erik Vernet sat with BioAge on a panel titled “Indications for longevity biotech: Pharma partnership for age-related drug discovery.” Both companies were already treating aging as an area for partnership, before GLP-1s became the conference’s main character.

ARDD 2024 — GLP-1 enters the scientific program. Jens Juul Holst, one of the foundational GLP-1 scientists, asked whether GLP-1 receptor agonists could ameliorate the metabolic complications of aging. Marie Kveiborg of the Novo Nordisk Foundation spoke on translating discoveries into the clinic. Lilly’s Jonathan Matthew Wilson joined a panel on sourcing aging therapeutics.

ARDD 2025 — the shift toward organ protection. Novo’s Lotte Bjerre Knudsen gave “Organ Protection with GLP-1 Receptor Agonists,” framing drugs that began in diabetes and obesity and had expanded into cardiovascular, liver, and renal protection: a disease-targeted therapy becoming a broader healthspan intervention. Lilly’s Berthil Clasen joined “How do we advance longevity in pharma in a credible way?”

ARDD 2026 — the “war” begins: Both Lilly and Novo showed human clinical data showing GLP-1s effects on aging clocks.

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1. Lilly vs. Novo: the race to lead in longevity therapeutics

The rivalry is usually described in obesity-drug sales, manufacturing capacity, and next-generation incretins. At ARDD 2026 another dimension became visible: which company can generate the more compelling evidence that its medicines affect biological aging.

Both are now investigating the aging-related effects of drugs they already sell. They are doing it with different biomarker technologies and different clinical datasets.

Eli Lilly: tirzepatide and 72 weeks of epigenetic aging

Kevin Duffin, vice president for aging research at Eli Lilly, presented an exploratory analysis of SURMOUNT-5, the trial comparing tirzepatide with semaglutide in people with obesity and without type 2 diabetes.

He opened with the case he thinks the drug already meets. Mounjaro for diabetes, Zepbound for obesity, and organ-level signals behind them: liver, kidney, heart-failure hospitalizations, and all-cause mortality in trials where the comparator was not placebo but dulaglutide, a weaker GLP-1.

“One of the definitions of a good drug, is one that shows improvements in multiple organ diseases. Well, I think we checked the box there. And then another condition for a good drug, is that we should see a reduction in mortality… and we see that too.”

The new piece of evidence is epigenetic. Lilly has not historically banked whole blood at later time points, which is why a company with tens of thousands of tirzepatide patients is only now showing clocks. “That’s on us,” he said, and guessed it was true at Novo too. “We’re all, I think, kind of scrambling a little bit to change our trials out to be able to collect this type of sample for biological aging clocka”

Lilly selected participants over 50, ranging to nearly 80, from a parent trial whose average age was the mid-forties and whose average HbA1c was about 5.6.

Over the 72-week treatment period, participants aged approximately 1.38 chronological years. The question was whether their biological age, as estimated by epigenetic clocks, followed the same trajectory. According to Kevin Duffin, the results suggested otherwise. Across multiple clocks, epigenetic age increased more slowly than chronological age, and some clocks even showed an absolute decrease. The magnitude varied considerably: first-generation clocks showed relatively modest effects, which Duffin described as around half a year less aging than expected, while some second-generation clocks showed larger effects exceeding 1.5 years relative to the expected trajectory. Measures of the pace of aging, including DunedinPACE, also declined. Two independent laboratories, Zymo Research and TruDiagnostic, produced broadly consistent findings. However, these were preliminary results from the tirzepatide arm alone, without a presented comparison to semaglutide or an untreated control group. As Duffin emphasized, some clock signals remained inconsistent, and the findings should be considered hypothesis-generating rather than proof that tirzepatide slows aging.

Duffin put the magnitude in perspective:

“All the clocks are telling a consistent story that we’re seeing a reduction in age. It’s not the panacea. It’s not like we’re going to reduce age by 30 years or something, but it’s a significant reduction.

The organ clocks offered another intriguing result. Of the organ systems assessed, only the lung showed an increase in predicted epigenetic age, which was not statistically significant. The heart, immune system, kidney, and liver showed decreases, broadly consistent with the clinical benefits Lilly has observed across these organ systems in its trials. Duffin was particularly interested in whether DNA methylation could predict measurable clinical changes. In several cases, it did: methylation-derived estimates were consistent with observed changes in BMI, waist-to-hip ratio, HbA1c, fasting glucose, triglycerides, LDL particle size, HDL particle size, apoA1, and HDL cholesterol, sometimes even approximating the magnitude of those changes. But the predictions were not universally accurate. For sex hormone-binding globulin, a TNF receptor, and BCAM, methylation-based predictions suggested an increase, whereas the measured protein levels actually decreased. This highlighted both the potential of epigenetic profiling to inform drug development and the limitations of treating methylation-derived estimates as substitutes for clinical measurements.

“The epigenetics is not perfect yet, and I think the clocks still have to do some refinement to make sure that they really do align with the real clinical data.”

He also said the substudy was small, some clock signals were discordant, follow-up was short for a chronic drug, and the clocks were not trained for treatment or for the same patient over time.

“I look at this as hypothesis generating. It’s not like, oh, the clock says this, and so that’s what it is.”

For now the findings support further measurement. They are not a claim that tirzepatide has been shown to reverse human aging. The competitive tell was the withheld arm. Lilly has the only head-to-head the market actually cares about, and did not open it.

Eli Lilly’s other SURMOUNT-5 dataset: proteomic organ age

Duffin pointed the room at a second analysis he did not give from the podium. Poster 13, “Organ-Specific Proteomic Age Changes in Adults with Obesity Treated with Tirzepatide,” is Corey James, Yanzhu Lin, Kevin Duffin, Colm O’Dushlaine and Axel Haupt. It is Olink plasma, not methylation, and it uses the Goeminne 2025 organ-specific and conventional proteomic clocks. It is also a different population from the over-50 epigenetic slice.

SURMOUNT-5 randomized adults with obesity, without diabetes, 1:1 to maximum tolerated tirzepatide (10 or 15 mg) or semaglutide (1.7 or 2.4 mg) for 72 weeks. The poster’s proteomics cohort is 301 randomized to tirzepatide and 297 to semaglutide, mean age 44.9 ± 12.9 and 44.7 ± 12.5, BMI 39.3 ± 7.2 and 39.5 ± 7.8, 64 percent women in both arms. Week 72 proteomics were available for 259 and 252. The published trial result cited on the poster is the one the market already knows: 20.2 percent weight loss on tirzepatide versus 13.7 percent on semaglutide at 72 weeks.

Predicted age tracked chronological age in the tirzepatide arm (r = 0.90, MAE = 6.0 years, n = 301) but with a systematic +4.5-year offset. Limits of agreement were −6.8 to 15.9 years. The offset was not a function of age in this cohort (r = 0.09, p = 0.134). Age acceleration was the residual from that fit. The gap between extreme quartiles was 10.17 years. Those quartiles separated on brain, pituitary and artery organ age. They did not separate on muscle, heart or lung. That is a different organ map from the epigenetic slide, where heart, immune, kidney and liver moved and lung did not.

Within the tirzepatide arm, seven of 18 organ and conventional clocks decreased significantly from baseline to week 72, referenced against the same 1.38 years of elapsed time. Semaglutide n is on the poster for trial context. The organ-age change figures are within-arm tirzepatide only. There is no placebo.

The poster’s own warning is the one the epigenetic talk did not have. ELN was the top-weighted protein in the artery clock and its strongest correlate with predicted age (r = 0.85). It rose more in people who lost more weight (r = −0.18, p = 0.003, n = 259) and was unrelated to systolic pressure at either visit. The authors say the artery clock in this cohort may be weight-loss-driven elastin turnover, not arterial aging. Blood pressure still diverged between the age-acceleration groups: 128.01 mmHg versus about 122 at baseline in accelerated versus decelerated agers, and 119.49 versus 109.57 mmHg by week 72, a gap they put at 9.92 mmHg.

Novo: Semaglutide across five trials and multiple organs

Alejandro Aguayo-Orozco framed it as the question the meeting had been circling. Pharma tests medicines one disease at a time.

“If we’re touching so many diseases, are we actually also touching something that is systemic across these diseases? Is it aging? Is it healthspan?”

His case for potential longevity effects of GLP-1 rested on how it works. It is both a gut hormone and a neuromodulator, released after a meal and also made by neurons in the brainstem. The receptor is not everywhere, the way the insulin receptor is; it sits on specialized cells across many tissues.

“When we activate the system pharmacologically, we’re not just simply flipping a switch. We’re actually creating a cascade of information and activities across these different organs. And that’s the kind of reach I think one would want to have if we want to influence healthspan and aging.”

It is also, he said, why a single clinical endpoint is hard to pin on one mechanism. Weight and appetite matter, but so do natriuresis, vascular function, blood pressure, and the liver. A major adverse cardiovascular event is unlikely to be any one of those alone. He organized the talk as four tests. The first was disease. Across five randomized trials and almost 32,000 patients treated for up to five years, he walked through a 20 percent reduction in major adverse cardiovascular events in a population without diabetes, better symptoms and six-minute walk distance in obesity-related heart failure with preserved ejection fraction, a 24 percent lower primary kidney composite in FLOW (stopped early for efficacy), and a 14 percent lower MACE rate with oral semaglutide in SOUL. Gastrointestinal effects were the most common adverse events, generally mild or moderate.

The third test, survival, was the one he treated as the integrative endpoint.

“If semaglutide was acting on aging, we would also expect to see an effect on the most integrative endpoint of all, all-cause mortality, not only cardiovascular related mortality.”

Pooling six outcome trials and more than 38,000 patients, he reported an 18 percent reduction in all-cause mortality. Encouraging, he said, not definitive.

The fourth test was biology. In up to about 10,000 patients with Olink proteomics, roughly one-to-one against placebo and followed from four months to three years, organ-age clocks moved. Heart and kidney scores were lower on semaglutide than placebo at the first measurement in all five trials, across two formulations and three doses. Other organs were mixed early and more consistently lower later. An early rise in an adipose clock looked, in the Q&A, like remodeling during the period of fastest weight loss — leptin and related proteins — and later flattened or reversed. A proteomic frailty score did not move early, then was lower from one year onward in every trial. He was clear that this is not grip strength.

The obvious objection is that GLP-1 drugs make people eat less. Mediation plots for the heart and kidney clocks, he said, did not show the shift running through weight change, glucose, or hsCRP.

“The effect that semaglutide has on reducing these clocks compared to placebo is not mediated by these three parameters… They’re seeing something different.”

He immediately narrowed that claim: it is not proof the effect is independent of weight loss, only that those three measures are not what the clocks are registering. In the Q&A he said individual proteins do show weight-mediated effects, especially early, and that later organ-age benefits still did not appear to be explained by weight change at one year and beyond. A heart-clock reduction mediated up to 40 percent of the cardiovascular-death reduction and up to 36 percent of the all-cause mortality reduction, and less of MACE.

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2. Novartis: why regenerating tissue is not a longevity drug

While Lilly and Novo presented biomarkers, Novartis offered the scar tissue. Fiona Marshall, president of biomedical research, used the company’s Diseases of Aging and Regenerative Medicine group, DEAR, to explain why one pathway and one tissue is no longer the plan.

“Our aim is not to extend the natural lifespan, but very much focused on targeting pathways of aging as a major risk factor for the core disease areas that Novartis already is interested in.”

Two programs, both taken to phase 2, made the point.

LNA043 was built to reawaken fetal cartilage development in osteoarthritis. A phenotypic screen produced an angiopoietin-like peptide. In patients undergoing autologous cartilage implantation, MRI showed defects filling against placebo. In established osteoarthritis, MRI again showed cartilage coming back. Commercial colleagues then said nobody would pay for a prettier scan.

“What you actually needed was less pain… and by the way, there’s already pain drugs, so it has to be better than the existing pain drugs. And you would also want improved mobility. Unfortunately, although we were able to see regeneration of cartilage in the knee, that did not correlate with improved pain scores or improved function. You could repair the cartilage, but the underlying disease was still there.”

Bimagrumab, an activin-receptor antibody, grew muscle. In a cast-immobilization proof of concept, lean mass came back once the cast came off. In sarcopenia patients, mass did not become mobility, and it did not become less frailty.

“It wasn’t just about regrowing cartilage. It wasn’t just about regrowing muscle. You had to think of this in the context of the whole system… You probably needed more exercise. There were behavioural things. You probably needed nutrition changes. It’s not just about regeneration. We must think much more about resilience.”

Single drugs against individual aging pathways, she said, are not going to work. The goal is a regenerative medicine plus something that stops the process that ate the tissue, timed before degeneration is the disease, with an endpoint a payer already understands. Healthspan, in her definition, is dull on purpose: still mobile, still cognitively intact, still able to work. Her mother died in her nineties with “old age” on the certificate. “Which is something I aspire to.”

The positive control she held up was not a Novartis molecule. It was exercise. She argued the Alzheimer’s curve for high daily activity is in the range of APOE4, maybe past it. The trap is circular. Osteoarthritis and sarcopenia are why older people stop moving, which is why their Alzheimer’s risk then rises.

DEAR’s method from here is longitudinal human data. Novartis has stacked decades of trials, including cardiovascular outcome studies and Alzheimer’s programs, into an internal store called Data42. CANTOS, the canakinumab inflammation trial, is the example she likes: a cancer signal too heterogeneous to confirm, then a proteomic signature, from collaborator Charlie Swanton, that might have shown which lung cancers inflammation was driving. The next layer is other people’s data and a collaboration with BioAge on the exercise response as a source of targets. Animal models, she said, can show a pathway. They are a bad description of human aging, and almost none of them get Alzheimer’s.

A cross-disease group is already building foundation models, kidney first, then neurodegeneration. She wants aging data dropped into those models rather than kept in a longevity silo.

The lesson is the counterweight to the clocks. A patient does not benefit because an MRI shows more cartilage. A person does not benefit because a blood algorithm prints a younger age. The question is whether they are healthier, more functional, or less likely to develop serious disease.

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3. China’s biotechnology acceleration is no longer a slide at the back

One of the most unexpected discussions by Big Pharma for me was not about drugs, but about China. The panel moderated by Alice Park of TIME included Stéphane Bancel, CEO of Moderna; Fiona Marshall President of Biomedical Research at Novartis; Ariel Feldstein, Pfizer’s chief scientific officer for internal medicine,; Christophe Weber, former chief executive of Takeda, and Elcin Barker Ergun, chief executive of Menarini.

Stéphane Bancel: the U.S. needs to wake up on trials

“We need to wake up on clinical trials. When you spend months negotiating with Harvard and then going to negotiate with Yale, and everybody has their own thing, but going to China, it’s the same thing for everybody… We don’t see a lot of lawyers when we go to China to negotiate a clinical trial.”

Dr Bancel was explicit that speed is not a license to cut safety. “None of us wants to cut a corner on safety.” The waste, in his telling, is repeating the same negotiation at every hospital. Asked what he was most wary of conceding:

“Betting against China is a very arrogant strategy. If you look at what they are building… people are smart, well educated, they work really hard, and you give it some compounding, and you know how this story finishes.”

He also pointed at two combinations Moderna is actually looking at, both of them lifestyle plus a drug: exercise multiplying vaccine response in older people, and fasting-mimicking diets before chemotherapy or checkpoint blockade.

Christophe Weber: AI plus China is a flood, and trials are the dam

“If you add the AI dynamic plus China, we will never have seen so many molecules in the history of pharma. The challenge, and somehow the bottleneck, is the clinical trial.”

China, he said, is not yet consistently first-in-class. It is already very good at best-in-class on a known target. The data are strong. A China-only trial still may not reproduce in a U.S. population. The old consolation, that China engineers and the West discovers, is the one he told the room to retire.

About 30 percent of drug failure, he said, is the trial rather than the molecule: underpowered, sites not run the same way, the wrong patients. AI can design a better study. It cannot enroll it. His guess was that R&D productivity more than doubles in five years, and that the new scarcity is which molecule you pick.

On prevention as a business, he was structural rather than scientific.

“If we are serious about prevention and aging, it should create a completely different paradigm. The issue right now is the same FDA managing treatment and prevention, the same healthcare systems, the same physicians — but it’s a totally different paradigm.”

Menarini, Pfizer, Novartis: use the science, keep the scientist

Elcin Barker Ergun described the other half of the compression. Working with Insilico Medicine, Menarini took an epigenetic target and a second oncology molecule from a ten-to-fifteen-year discovery cycle into two or three years. They are in the clinic. A 4,000-patient adjuvant breast cancer trial finished in 18 months, mostly because patient-finding finally caught up with protocol writing.

Ariel Feldstein’s caveat was the one the builders usually skip. The models are not short of data. They are short of the right question, and the scientist has to stay in the loop. “The co-scientist approach is the way we see it.”

Asked about Novartis licensing a Chinese CAR-T after suspending eight of its own CAR-T trials, Marshall declined the framing.

“We’re a global company. We go where there’s good science and good assets… we are indeed increasingly seeing that in China, with additional clinical data. That’s what we get excited about.”

Mark Cobbold, who builds AstraZeneca’s cell therapy business, thought the aging version of this race also tilts to China: the scale of the scientific workforce, ten- and twenty-year plans, life sciences named a national priority, and a one-child generation about to look like Japan’s age structure. His own conversion was an in vivo CAR-T dataset he was sure would fail, because the textbooks said you needed lymphodepletion. The first patients expanded anyway, on a par with autologous CAR-T. If aging turns out to be an epigenetic or genetic change rather than a missing small molecule, “we’re starting to have the tools… at the moment everyone focuses on small molecules. I don’t quite know why.”

China is no longer being discussed as a manufacturing site or a cheap place to run a study. Executives are treating it as a source of assets, capabilities, and partnerships. They also said a China-only dataset may not travel. The strategic point survived that caveat.

4. What’s the current reality for not Big Pharma drug developers?

The licensing panel also took the business-model question: if companies succeed at preventing age-related disease, what happens to a model associated with treating people after they are sick?

Jonathan Levy, senior director of strategy, at Astra Zeneca put the language problem first. “If a company is coming to us and saying there’s validation, or this is a validated target or a validated drug, it needs to be very specific what you’re talking about.” A screen, a single-cell clock, a proteomic signature, a senescence pathway that might touch fibrosis: none of that is validation in the sense a partner can underwrite. Nikolai Kulahin, a global project lead at Novo, was blunter about the bar. A compound that reduces senescence in a dish is not enough. A compound that prolongs life in mice, mechanism unknown, is not enough. Genetics help, because they let you look across traits, but the conversation always rotates back to therapeutic efficacy inside an established area. Longevity, he noted, is not a disease, so the asset still has to be packed into one (Dominika here - it might be changing - see the previous post on the Goverment). He also drew the healthspan line the field keeps dodging:

“We’re not necessarily wanting to give people more life. We would rather ensure that they have a better quality of life at the end.”

Avi Spier, in business development and licensing at Novartis, refused the idea that proof of concept is a single experiment. Companies arrive saying they have efficacy and safety and then cannot understand why he is not excited.

“What I’m looking for is proof of concept that this is going to do all of that and beat the competition and be the best standard of care.”

Genetic evidence, a translatable mouse model, a tool compound that does exactly what you say it does: any of those can count, if they support a target product profile worth an investment. David Berry, managing partner of Avren Capital and a former Flagship general partner, came at the same word from the other side of the table.

“I’m not looking for the coolest science paper. I’m not looking for the prettiest graph. I’m looking for a way where I can put a certain amount of money in and generate a return, usually at least tenfold.”

Pharma, in his telling, is hunting two things at once: the next ten-billion-dollar drug, “where’s the next GLP-1,” and drugs so predictive that today’s data makes the next stage feel inevitable. “Proof of concept is how do we prove that this is ten billion dollars, or how do we prove that it’s really predictive.”

Claris Munksgaard, director of business development and licensing at EMD Serono, described what a package has to survive. Pharma does “excruciatingly exhaustive” diligence: data rooms, patient-level data, its own analyses, sometimes an audit before signature. The failure mode she sees most is biologists picking the in vivo model that tells the best story. Parkinson’s alone has roughly ten. “Choosing certain in vivo models that perhaps give them the best story to tell, and maybe the best data to show, actually does more harm than help.” She wants the gold-standard model, clean PK and safety, target engagement, a flicker of efficacy, and above all differentiation. She also wants an early FDA conversation, even when it is not required, and a development plan that can actually earn the label you are selling. Commercial logic bites earlier than founders expect. A molecule aimed at a rare oncology price and a broad immunology price cannot have those revenues added together. “They cannot be both an expensive and a lower-cost drug,” so the paths are alternatives, not a sum.

On fit, the panel inverted the usual late-stage wisdom. Berry argued culture matters more before the clinic, because a late asset often sheds its people within a year, while a preclinical partnership is “tying basically a wedding knot for five years.” Milestones someone else controls are deferred compensation. If you do not trust them to run the work, pay you, and not “weasel” around the letter of the agreement, the structure is a problem. Levy added that joint steering committees outlive the close, plans break, and the industry is small enough that the relationship follows you.

The takeaways were practical. Claris Munksgaard: “talk to the FDA early, and talk to pharma early, even when you are two years out. Pharma moves slowly, like an aircraft carrier.”

Berry: sell what they already want to buy.

“Everyone will tell you exactly what they want to buy. Often what you find with founders is that they are so stuck in their way. Persistence is the number one feature of a founder. But if you’re trying to sell something that a pharma doesn’t care about, they’re going to continue to not care about it after you leave the room.”

Spier asked founders to map the competitive field better than the partner can, including the quiet problems in rival programs. Levy’s version of the same plea was Jerry Maguire. He sees hundreds of non-confidential decks a year. “Help us do our job. Make my job easy.” A deck that notices three Phase 2 drugs already in the pipeline and explains the combination biology will get read. A deck that says “maybe this is interesting” will not.

On intellectual property, Berry was the least diplomatic. Partners will not always say it first, but “IP is the most important thing,” because if diligence finds a hole, they do not need you. Put the value on a silver platter, in the indications they already spend time on, and do not skip the boring assays. He described starting Seres Therapeutics, showing 29 of 30 patients clinically cured in Phase 1, and still being asked for the mouse data. “Last I checked, we were developing drugs for people. You may have cutting-edge stuff. Make sure you have both your cutting-edge stuff and the boring old-school stuff.”

Phil McGurk said that aging still carries biology risk and regulatory risk. There is no agreed endpoint. There is no crowd of bidders.

“Doing a deal that’s focused on longevity, you’re taking on an enormous amount of risk, and whenever we’re taking on an enormous amount of risk, we don’t want to pay a lot up front.”

What ARDD 2026 actually changed

There is a certain irony in the fact that some of the most compelling evidence for pharmacologically influencing biological aging is now coming from drugs that were never designed to target aging in the first place. Perhaps this tells us something about the limitations of organizing medicine around diseases rather than the biological processes that connect them. But it also raises an uncomfortable question for the longevity industry: if drugs developed for conventional indications can demonstrate benefits across multiple age-related conditions, what must a therapy developed specifically for longevity prove to justify its existence? A younger biological-age score will hardly be enough. It will need to deliver something that existing medicines cannot, whether that is preventing diseases before they emerge, restoring lost function, or extending healthy life in people who are not yet patients. The difficulty is that our pharmaceutical and regulatory systems are exceptionally well equipped to recognize and reward the treatment of disease, but much less prepared to value the preservation of health. This is not merely a scientific problem; it shapes which experiments are funded, which endpoints are measured, which companies receive investment, and ultimately which medicines are ever developed. The next chapter of longevity biotechnology may therefore depend as much on rethinking the incentives and evidence standards of medicine as on discovering new aging pathways. The best ending quote is the one by Dr Kevin Duffy:

“I see many companies that are trying to develop aging programs and aging drugs. Novartis, and Novo, and many of the others. I say, bring it on. We’re ready for it. We will compete with you.”

We’ve discussed FDA and goverment in part 1, Big Pharma in part 2; Subscribe for the biggest scientific news from ARDD 2026 in the coming days!

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This week, I’ll be unpacking the biggest news across three fronts: regulatory, scientific, and commercial.

Part 1: Is the FDA finally opening the door to longevity therapeutics?

For decades, aging has remained outside the FDA’s traditional drug-approval framework. At ARDD 2026, senior FDA officials discussed what it would actually take to approve therapies targeting aging, questioned whether aging even needs to be classified as a disease, and revealed that aging and longevity will officially enter the agency’s regulatory-science priorities.

What exactly did they say and how close are we to the first drug approved for targeting aging itself? Let’s go straight to the source, with direct quotes from the FDA leadership.

And stay tuned. The FDA was only the beginning.

FDA put aging and longevity on its regulatory-science agenda

For years, the central question in geroscience has been whether the FDA could ever approve a therapy aimed at aging itself rather than a single disease. Without a regulatory pathway for aging, there has never been a clear business model for a scalable longevity company that did not involve choosing an age-related disease as its first indication, partially diluting the research away from “pure aging.”

The challenge has been both scientific and regulatory. Aging is still not particularly well understood, and there are no universally agreed-upon endpoints that reliably demonstrate the modulation of aging itself. Even promising approaches, such as proteomic aging clocks, have yet to be accepted as validated surrogate endpoints for regulatory approval. For years, regulators largely stayed away from the field despite its enormous potential: the science was simply too early. But recent developments, particularly in next-generation aging clocks and biomarkers, have begun to capture regulators’ attention.

At ARDD 2026, that change became visible.

For the first time at a longevity-focused event, a panel of senior FDA officials explicitly discussed potential regulatory pathways for longevity therapeutics. The panel brought together Lowell M. Zeta, Acting Chief of Staff, Office of the Commissioner, FDA; Jeffrey Siegel, M.D., Director, Office of Drug Evaluation Sciences, Office of New Drugs, CDER, FDA; Justin Penzenstadler, M.D., Associate Director (Acting), OCHEN/OND/CDER, FDA; and Steven Kozlowski, M.D., FDA Chief Scientist. The discussion was moderated by Andrew Brack, Program Manager at ARPA-H.

The most consequential announcement came from Dr Kozlowski, who confirmed that the agency is preparing a new document outlining its regulatory-science priorities, with aging and longevity explicitly included:

“Aging and longevity will be in the agency’s focus areas of regulatory science, planned for early fiscal 2027. The FDA is not only a hurdle. One badly misread result can set the field back for years.”

This represents a significant departure from the field’s historical position on the regulatory sidelines. Rather than dismissing aging as too poorly defined to warrant regulatory engagement, the FDA is beginning to treat it as a scientific challenge that deserves a structured approach.

As Dr Kozlowski further explained:

“The Office of the Chief Scientist is here for the science required to translate aging biology into a pathway that encourages development and still assures safe and effective products.”

Importantly, the discussion suggested that formally classifying aging as a disease may not be a prerequisite for progress. Dr Lowell Zeta challenged the assumption that the entire field must first settle this longstanding debate:

“I question whether we need to resolve whether aging is a disease in order to make progress. Going down that track may narrow us into tools that were not designed for this.”

His argument points toward a more pragmatic regulatory strategy: rather than waiting for consensus on whether aging itself constitutes a disease, developers could begin establishing clinically meaningful outcomes that reflect the effects of interventions on age-related functional decline.

That approach, however, requires much more than showing that a treatment makes a biological clock run backward.

The FDA panel sketched a plausible route toward approval, beginning with hard clinical outcomes, such as the prevention of age-related comorbidities or mortality, in carefully selected older populations. Measures such as intrinsic capacity, functional decline, and multimorbidity could eventually provide more practical endpoints and shorten clinical trials, but only once they are rigorously linked to meaningful clinical benefits.

Dr Jeffrey Siegel drew a crucial distinction between biomarkers that predict aging-related risk and those that could actually support regulatory approval:

“A prognostic biomarker sorts risk. A surrogate must also change with treatment, and that change must reflect later clinical benefit. Define the population, define an outcome across those domains, and show slower progression than control. That could be an indication: effect on how patients function, feel, and survive.”

This distinction matters enormously for longevity biotechnology. A biomarker that accurately predicts mortality or biological age is not automatically a valid endpoint for a therapeutic trial. Developers must demonstrate that an intervention-induced change in the biomarker reliably predicts a corresponding clinical benefit. Until that relationship is established, even the most sophisticated aging clocks cannot independently establish clinical efficacy.

But the FDA officials were not simply outlining obstacles. They were actively encouraging the field to engage with the agency and begin developing the evidence required for new regulatory pathways.

Dr Justin Penzenstadler offered particularly direct advice to commercial sponsors:

”We’re trailblazing for trials and endpoints. The best way to get feedback on trials and endpoints is to send me a send me an IND, send FDA an IND, send a protocol, and we’ll take a look. That’s the absolute best way to interface with FDA for for commercial sponsors”

He also emphasized the need for collective action and real clinical data rather than prolonged theoretical discussions:

“We are the umpire, not the coach. Form a pre-competitive consortium, put the same biomarkers into real trials, and send us a protocol under an IND. Theoretical questions will come back as a review issue.”

The implication is that longevity companies should not wait for the FDA to independently define an entirely new regulatory framework before beginning development. Instead, the field needs to bring concrete protocols, standardized biomarkers, and clinical evidence to the agency so that regulatory standards can evolve alongside the science.

Dr Zeta reinforced that the FDA’s role is not to design the field’s clinical development programs, but to provide a predictable framework for evaluating them:

“We are the umpire, calling balls and strikes. But we also want to give developers predictability. That is where we need your help.”

Together, these remarks point to an important change in the relationship between longevity biotechnology and its regulator. The FDA is signaling a willingness to engage, but it is also placing responsibility on researchers, clinical developers, and industry consortia to generate the evidence needed to establish credible endpoints.

This is not yet recognition of aging as an FDA indication, nor does it mean that biological aging clocks have been accepted as surrogate endpoints for drug approval. But it is a meaningful, milestone-like precedent that senior FDA leadership is now publicly treating aging as a legitimate regulatory-science problem to solve, discussing what an approvable clinical outcome might look like, and explicitly inviting developers to help build the pathway.

For an industry that has spent years wondering whether the regulator would ever come to the table, that alone is a milestone.

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Goverment is getting involved in longevity

The FDA was not the only senior government voice discussing longevity at ARDD 2026. Admiral Brian Christine, the 18th Assistant Secretary for Health at the U.S. Department of Health and Human Services (HHS), delivered a keynote address on how advances in aging science could be translated into clinical practice and public health policy.

Admiral Christine is a physician and urologist with approximately 35 years of clinical experience, particularly in men’s health. Appointed under President Donald Trump and serving within HHS under Secretary Robert F. Kennedy Jr., he also leads the U.S. Public Health Service Commissioned Corps, a uniformed service of more than 5,000 public health professionals. His office helps develop, implement, and communicate health policy across HHS, connecting priorities that span agencies such as the FDA, NIH, and CDC.

His message at ARDD centered on a fundamental change in how American healthcare should approach aging: moving from treating individual diseases after they emerge toward preventing multiple chronic conditions and preserving function throughout life.

Christine argued that the United States has extraordinary biomedical research capabilities but has struggled to translate scientific advances into population-level health improvements. He described the American healthcare system as reactive rather than proactive, treating hypertension, diabetes, cardiovascular disease, and obesity separately, despite the shared biological mechanisms that often underlie them.

For longevity biotechnology, this creates an important opportunity. If interventions targeting fundamental aging processes can delay several diseases simultaneously, they could fit into a broader healthcare strategy built around prevention rather than disease-by-disease treatment.

However, Admiaral Christine also delivered a clear warning about the growing enthusiasm surrounding aging biomarkers and biological clocks:

“A biological age clock moving backward is interesting, and a biomarker changing is interesting. But interesting is not always the same as clinically clinically meaningful.”

His point echoed the FDA panel’s distinction between promising biomarkers and validated clinical endpoints. Reversing a biological aging clock is not sufficient evidence that an intervention improves healthspan. Researchers must establish whether those changes translate into outcomes patients actually care about: preserved mobility, cognitive function, independence, and fewer years lived with disability.

Christine also addressed the rapidly expanding market for longevity interventions, including peptides, hormone therapies, supplements, biological-age testing, and other products frequently promoted through wellness clinics and social media. While supportive of innovation and reassessing established medical assumptions, he cautioned against allowing commercial enthusiasm to outpace clinical evidence:

“But neither should enthusiasm on social media become clinical practice simply because an intervention is new, exciting, or it’s biologically plausible.”

Equally important was his emphasis on accelerating the translation of credible discoveries into clinical practice. Admiral Christine argued that generating strong scientific evidence is only the beginning. Government agencies, regulators, healthcare providers, and payers must work together to ensure that validated interventions actually reach patients.

“Because evidence, when it’s trapped in a journal, doesn’t improve population health.”

He called for a faster process connecting scientific discovery, replication, regulatory evaluation, clinical guidelines, reimbursement, physician education, and patient access.

Together with the FDA panel, the message from ARDD 2026 was clear: government officials are increasingly willing to engage with longevity science, but the field must demonstrate clinically meaningful outcomes and build the evidence needed to translate promising interventions into accessible, preventive medicine.

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Goverment agencies are tying it together: ARPA-H is hunting endpoints

While the FDA discussed what it would take to approve longevity therapeutics, Andrew Brack, Program Manager at the Advanced Research Projects Agency for Health (ARPA-H), presented a government-funded initiative designed to generate exactly the evidence regulators need. ARPA-H, a federal biomedical research agency within HHS, is investing up to $144 million over five years in PROSPR, a program designed to develop clinically meaningful endpoints for aging and test therapeutics that directly target aging biology.

The central challenge is that molecular aging clocks can change quickly but have not been validated as predictors of clinical benefit, while traditional endpoints such as disease incidence and mortality require lengthy, expensive trials. PROSPR aims to bridge this gap by developing a standardized intrinsic capacity score, combining functional measures such as walking performance, lung function, and cognition into a potential clinical trial endpoint. Rather than immediately seeking approval for biological aging clocks as surrogate biomarkers, PROSPR is pursuing FDA qualification of a Clinical Outcome Assessment (COA), which could eventually provide a standardized measure that multiple drug developers can use in longevity trials.

Crucially, this is not just a biomarker-development exercise. The program includes a trial involving approximately 1,200 adults aged 60–75 without the target diseases, investigating whether repurposed drugs, including GLP-1 therapies and dapagliflozin, improve intrinsic capacity. Four additional teams are advancing experimental longevity therapeutics toward early clinical trials, including interventions targeting mTORC1 and LINE-1 retrotransposons.

Eight months into the program, Brack reported that 15 longitudinal datasets had already been integrated, discussions with the FDA about qualifying the functional endpoint had begun, and clinical trial preparations were advancing.

The significance is that the U.S. government is not merely discussing how longevity drugs might eventually be approved: through ARPA-H, it is funding the clinical infrastructure, endpoints, and therapeutic trials needed to make such approvals possible.

Coming tomorrow: The Big Pharma battle for longevity.

Two pharmaceutical giants are racing to become the pioneers of longevity therapeutics and both arrived at ARDD 2026 with human clinical data suggesting their drugs could turn back biological aging clocks (going into Insilico’s Rentosertib’s footsteps?).

Who will emerge as the leader in the race to develop the first generation of longevity therapeutics? And how convincing is the science behind their claims?

Stay tuned for Part 2. The race for longevity has officially entered Big Pharma territory.

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“Best” is seemly a subjective question, but AIs came up with a relatively objective set of benchmarks such as: meeting with the strongest unpublished science, the largest audience, the most famous speakers, the greatest influence on drug development, or simply the event everyone in a particular professional tribe feels they cannot miss.

The terms “Aging research” and “longevity” became increasingly diluted over the recent years. One is interpretation is classical gerontology: demography, psychology, social policy, care, epidemiology and the lived experience of older adults. Another is the basic biology of aging. A third is geroscience translation: biomarkers, trials and interventions intended to delay multiple age-related diseases. A fourth is longevity biotechnology: companies, platforms, drug pipelines, investment and partnering. A fifth is clinical longevity medicine, a young category with uneven evidence standards.

A defensible evaluation should therefore ask at least five questions:

Scientific signal: Are leading investigators presenting important, preferably new, work? How much of the program is selected from scientific abstracts rather than invited for visibility?

Field centrality: Does the meeting cover the core biology broadly enough to shape researchers’ agendas, rather than merely showcasing a specialty?

Translational leverage: Are the people who can move ideas into trials like pharma R&D leaders, biotech operators, regulators, clinicians and funders actually in the room?

Convening power: How international, cross-institutional and cross-sector is the audience? Does the meeting create collisions that would not occur inside a single scientific society?

Evidence quality: Are attendance, selectivity and impact claims independently verifiable? Do concrete collaborations, publications or programs follow from the event?

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Five LLMs picked ARDD. What were they picking up on?

Disclaimer: I am heavily involved in ARDD on multiple fronts, from speaking to volunteering

Using my non-biology, non-longevity friend’s paid accounts, I asked ChatGPT, Claude, Gemini, DeepSeek and Work Buddy “What is the number 1 conference in aging research in the world today?” and they all highlighted the Aging Research and Drug Discovery meeting, ARDD, as a leading choice. The agreement was strongest when the question concerned the intersection of aging biology, therapeutic development and industry.

ChatGPT was particularly direct:

“If I had to name one aging-research conference as #1 globally in 2026, I would pick ARDD.”

This was an informal comparison of five recorded answers, rather than a controlled benchmark. Still, their explanations raise two interesting questions: what makes ARDD stand out, and what exactly does it mean when several AI assistants arrive at the same recommendation?

What is ARDD?

The event was started by Dr Alex Zhavoronkov and began as a small forum in Basel in 2014, operated within larger conferences through 2019 and became independent in 2020. The 2025 Copenhagen meeting drew more than 1,000 people onsite and more than 10,000 online. Those figures indicate substantial reach for a conference focused specifically on longevity biotechnology. Unlike many conferences, ARDD has its own transparency statement.

The 2025 program brought together fundamental aging researchers, biotech companies, senior pharmaceutical scientists, top journal editors, government represerntatives eg form ARPA-H and even Nobel laureates Morten Meldal and Michael Levitt, alongside big pharma executives from Eli Lilly, Novo Nordisk, Novartis, Biogen.

ARDD has a track record of shaping broader pharmaceutical agendas. After the 2025 meeting featured debate over GLP-1 receptor agonists and longevity with representatives from Novo Nordisk and Eli Lilly positioning their peptides as having potential longevity benefits, Nature Biotechnology published an editorial asking whether GLP-1s are the first longevity drugs. ARDD publicity portrays this as evidence that the meeting shaped the agenda.

ARDD also keeps a tradition of publishing the proceedings in peer-reviewed journals, beginning in 2018, which adds to the credibility of the meeting.

• 2018 — “Aging and drug discovery” — report/synthesis of the 5th Annual Aging and Drug Discovery Forum (ARDD 2018). Aging, 10(11):3079–3088. DOI: 10.18632/aging.101646. Paper (Københavns Universitets Forskningsportal)

• 2019 — “Latest advances in aging research and drug discovery” — synthesis of the 6th ARDD meeting (2019). Aging, 11(22):9971–9981. DOI: 10.18632/aging.102487. Paper (PubMed)

• 2020 — “ARDD 2020: from aging mechanisms to interventions” — report from the 7th ARDD meeting (2020). Aging, 12(24):24486–24503. DOI: 10.18632/aging.202454. Paper (PubMed)

• 2022 — “Meeting Report: Aging Research and Drug Discovery” — report from the 8th ARDD meeting (2021). Aging, 14(2):530–543. DOI: 10.18632/aging.203859. Paper (Vrije Universiteit Amsterdam) and following collection in Frontiers dedicated to research presented at 8th ARDD: https://www.frontiersin.org/research-topics/25628/the-8th-aging-research-and-drug-discovery-meeting-ardd-2021

• 2024 — “Longevity biotechnology: bridging AI, biomarkers, geroscience and clinical applications for healthy longevity” — generated from the 10th ARDD meeting (2023). Aging, 16(20):12955–12976. DOI: 10.18632/aging.206135. Paper (Aging-US) (I had the honor of being the co-first author)

• 2025 — “Innovations in aging biology: highlights from the ARDD emerging science & technologies workshop” — report from the Emerging Science & Technologies workshop at ARDD 2024. npj Aging, 11:8. DOI: 10.1038/s41514-025-00193-5. Paper (Københavns Universitets Forskningsportal)

• 2026 — “Toward actionable interventions in human aging (12th ARDD meeting, 2025)” — comprehensive report from ARDD 2025. Aging, 18(1):282–302. DOI: 10.18632/aging.206368. Paper (Københavns Universitets Forskningsportal)

There are also credible signs of agenda visibility. Nature Aging includes ARDD on its conference calendar alongside AGE, GRC, CSHL, IAGG, BSRA and other meetings.

Finally, ARDD is organized by KOLs in the field, with an extreme attention to detail, literal weekly meetings for a whole year prior to the event. It takes an insane amount of work, and it delivers - there are people who raised at ARDD, entered research partnerships, and even came up with ideas for their companies.

Why ARDD, according to LLMs?

The most consistent theme was translation: connecting discoveries about aging with the people who can develop, test and finance interventions.

DeepSeek put it succinctly:

“For translating science into medicine, ARDD is the clear leader.”

Gemini similarly emphasized:

“Translating basic aging biology into clinical therapeutics, AI-driven drug discovery, and biotech commercialization.”

These descriptions have a concrete counterpart in the announced 2026 program. Kevin Duffin of Eli Lilly is scheduled to discuss tirzepatide and aging clocks; Nikolaj Roed of Novo Nordisk will address the evidence and unmet needs around GLP-1 therapies and healthy aging; and Marco Quarta of Rubedo Life Sciences will discuss clinical translation of a GPX4-targeted approach to skin aging and related conditions. These are specific development questions about how aging biology might become medicine. Novartis’s President of Biomedical Research, Fiona Marshall, will discuss drug discovery through the lens of aging biology, alongside a pharmaceutical leadership panel featuring Menarini CEO Elcin Barker Ergun, former Takeda CEO Christophe Weber and Pfizer’s Chief Scientific Officer for Internal Medicine, Ariel Feldstein. FDA officials will join ARPA-H’s Andrew Brack to discuss aligning clinical trials with regulatory requirements, while a dedicated workshop will introduce eleven XPRIZE Healthspan finalist teams. Scientific presentations include George Church on testing combinations of rejuvenation interventions and targeted delivery, and Tony Wyss-Coray on how circulating proteins reveal and regulate organ function. Investors from OrbiMed, Vida Ventures, Deerfield and Qiming also feature in the program. Together, these sessions connect the people uncovering aging mechanisms with those designing trials, evaluating evidence, financing development and bringing medicines to patients.

For someone developing a longevity therapeutic, that combination matters. Identifying a promising mechanism is only the beginning. A program also needs a suitable indication, credible measurements, clinical evidence and a path to patient access. A meeting that brings these conversations together has a particular value for translational researchers and founders.

The second recurring explanation was the mix of people. Claude described ARDD as:

“bridging academic aging biology with pharma/biotech”

The published speaker roster supports that description. It includes Vadim Gladyshev, David Sinclair, George Church, Tony Wyss-Coray and Steve Horvath, alongside C-suite representatives from companies including Lilly, Novartis, Pfizer, AstraZeneca and Novo Nordisk. Investors listed include i.a. Anthony Philippakis of GV, Kan Chen from Qiming Ventures and Avak Kahvejian of Flagship Pioneering.

The significance is the opportunity for different kinds of expertise to meet. A discovery that looks compelling in a laboratory can face very different questions from a clinician, a pharmaceutical development team or an investor. Putting those people in the same room can bring those questions into the conversation earlier.

The third theme was breadth. Work Buddy’s described ARDD as:

“bringing together basic science, clinical research, major pharmaceutical companies, and institutional investors”

That breadth also extends to the technologies entering longevity research. The 2026 program includes dedicated forums on longevity medicine, AI in drug discovery, pet and animal longevity, and virtual aging cells. The virtual-cell program features Omar Abudayyeh on virtual models of biology and health, and Jonathan Weissman on cell-state representations and cellular responses to perturbations.

Several LLMs nevertheless distinguished ARDD from meetings such as the Gordon Research Conference on Biology of Aging and Cold Spring Harbor’s Mechanisms of Aging, which they favored for more focused discussions of fundamental biology. The shared recommendation was therefore more specific than “ARDD wins every category”: its appeal was especially strong for people interested in moving between aging science and therapeutic development.

How do LLMs reach a recommendation?

Don’t get me wrong, I love ARDD with my whole heart and I was very happy when all LLMs agreed. However, a scientist in me started wondering: what parameters LLMs prioritize with making such descision? An AI assistant does not have to search the internet every time it answers a question. Its response can draw on information learned during training, the current conversation and, when available and used, external search tools.

During training, language models learn statistical relationships from large collections of text. Those relationships can encode factual information and associations between institutions, researchers and subjects. At response time, the model generates text conditioned on its instructions and available context. A familiar association can therefore appear in an answer without the model opening a current webpage.

Live search adds another source of evidence. A search-enabled LLM can retrieve information, incorporate it into its response and provide citations. Anthropic, for example, describes Claude’s web search as a way to bring current information into answers with links that users can check. Search availability does not establish that every answer used it, and the saved comparison does not provide complete search histories for all five assistants.

The broader research principle is called retrieval-augmented generation: combining knowledge stored in a model’s parameters with information retrieved from an external source. In their foundational 2020 paper, Patrick Lewis and colleagues found that their retrieval-augmented models generated more specific and factual language than a comparable model relying only on its parameters.

Applied to ARDD, a plausible explanation is that its public record supplies several mutually reinforcing signals: recognizable researchers, pharmaceutical participation, detailed programs and an explicit focus on therapeutic development. Those are also the criteria the recorded answers repeatedly mention.

Agreement across assistants needs similar care. Different systems may encounter overlapping information, including the same conference website or articles repeating an organizer’s announcement. Five recommendations can reflect a shared information environment; they do not automatically constitute five independent assessments.

Research by Mrinank Sharma and colleagues has also shown that AI assistants can favor answers aligned with a user’s views, a behavior called sycophancy; as mentioned before, I used my friend’s accounts, and she has nothing to do with biology, let alone longevity, to avoid this bias.

So why did the models agree?

The evidence supports all five major explanations, but not equally.

First, genuine signal. ARDD has assembled an unusually strong and visible cross-sector network. Its programs contain genuine scientific leaders and unusually senior pharma representation. In longevity biotechnology, the observable evidence favors it.

Second, shared information. All LLM answers repeat the same facts and category boundaries The relevant issue may be shared live-search sources as much as shared training data, especially because several cited pages are from 2026.

Third, search-engine visibility. Generic searches for the best aging or longevity conference prominently surface ARDD’s official site and press-release derivatives.

Fourth, successful marketing. ARDD has persistently described itself with a narrow but powerful narrative and surrounded that claim with recognizable institutions, speakers and companies. Its messaging is consistent enough to become the default sentence the internet knows about the meeting.

Fifth, category definition. Most models silently translated “aging research conference” into “longevity biotechnology and drug-discovery conference.” That interpretation privileges ARDD.

There is also an authority-signaling effect. A model can easily count famous names, Nobel Prizes, pharma brands and Harvard affiliations. It cannot easily measure the quality of a hallway conversation, the importance of an unpublished result or a conference’s reputation inside a small expert network. What machines can see shapes what machines call prestigious.

The question is no longer simply, “What do the models think?” It is: what did the internet make easiest for them to think? That’s why, if you work in PR or are building a personal brand, you should include AI crawlers in your audence and make sure your content is easy for them to pick up.

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For years, longevity biotechnology has had two largely separate worlds.

In one, researchers build aging clocks, algorithms that estimate biological age, from DNA methylation, proteins or other molecular data. In the other, pharmaceutical companies run clinical trials built around conventional disease endpoints: lung function, tumor size, glucose control, cardiovascular events.

Today, those worlds moved closer together.

A study published in Nature Biotechnology by the one and only Insilico Medicine team, applied six independently developed proteomic aging clocks to blood samples from a randomized phase 2a trial of rentosertib, a drug for idiopathic pulmonary fibrosis (IPF). Every clock detected a treatment-associated shift toward a younger proteomic profile somewhere across the tested doses and timepoints. The strongest cross-clock agreement appeared after four weeks of treatment.

That is a genuine first. To the best of current evidence, rentosertib is the first de novo drug candidate selected with aging biology in mind to produce a convergent signal across six proteomic aging clocks in a randomized human trial dataset.

This is the first systematic attempt to evaluate a new, purpose-built drug with several proteomic clocks at once, then connect their predictions back to dose, mechanism, senescence and a conventional clinical endpoint. It turns aging clocks from an interesting score into part of a drug-development workflow.

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Not another metformin story

Most drugs discussed as possible geroprotectors were not born as longevity drugs. Metformin began as a diabetes medicine. Rapamycin began as an immunosuppressant. Semaglutide was developed for diabetes and obesity. Researchers noticed their broader biology later and began asking whether they might also slow aspects of aging.

Rentosertib followed a different path.

Insilico Medicine used its PandaOmics platform to identify TRAF2- and NCK-interacting kinase, or TNIK, as a target connecting fibrosis with multiple hallmarks of aging. Its generative chemistry platform was then used to design a selective small-molecule TNIK inhibitor. The program moved from target discovery to a nominated preclinical candidate in roughly 18 months, according to the team’s earlier discovery-to-clinic Nature Biotech paper.

The disease chosen for development was IPF, a progressive and usually fatal scarring disorder of the lungs. IPF is not aging itself, but it is tightly age-linked and shares biology with aging: cellular senescence, chronic inflammation, altered nutrient sensing, extracellular-matrix remodeling and impaired tissue repair (read the paper on that, which I co-authored).

That makes IPF a practical regulatory doorway. Aging is not currently an approved disease indication. IPF is. A drug can therefore be developed against a recognized disease while researchers measure, in parallel, whether it also moves aging-related biology.

The original phase 2a trial randomized 71 people with IPF to placebo or one of three oral rentosertib regimens for 12 weeks: 30 mg once daily, 30 mg twice daily or 60 mg once daily. The study met its primary safety and tolerability objective. It also produced an exploratory lung-function signal: mean forced vital capacity rose by 98.4 milliliters in the 60 mg once-daily group, compared with a 20.3-milliliter decline on placebo. Again, this was the first time ever that a drug managed to reverse the effects of IPF in patients, rather than just slow the decline.

The new paper asks a different question of the same trial: did the drug make the patients’ molecular profiles look younger?

Six clocks enter the clinic

Forty-two trial participants, with a mean age of 67.1 years, had complete serum samples at baseline and at weeks 2, 4 and 12 and consented to the proteomic substudy. The researchers measured 2,841 circulating proteins with the Olink Explore 3072 platform and passed the resulting data through six clocks:

• ProtAge

• ipfP3GPT

• PAOPAC

• PAC

• OrganAge trained on chronological age

• OrganAge trained on mortality risk

These were not six cosmetic variations of one model. Some used traditional machine learning and others deep learning. Four were trained to estimate chronological age; two were trained against mortality. They also differed in their protein features and construction.

That diversity matters because aging clocks are notoriously capable of disagreeing. A result seen with one clock may reflect that model’s assumptions, technical noise or sensitivity to one biological pathway. Agreement among several clocks is harder to dismiss as a model-specific artifact.

Across 54 comparisons (six clocks, three treatment regimens and three post-baseline timepoints) 21 showed a statistically significant younger shift relative to placebo using the study’s exploratory false-discovery threshold of q < 0.10. At week 4 alone, 11 of 18 clock-by-regimen comparisons were significant.

The clearest single chronological-age result came from the 60 mg once-daily arm at week 4: all four chronology-trained clocks estimated a reduction of roughly 2.7 to 3.5 biological years relative to placebo. But the broadest agreement appeared with 30 mg twice daily, which was detected by both chronological and mortality-trained models. At that week-4 timepoint, five of the six clocks showed effect sizes pointing in the younger direction.

By week 12, the headline signal had not continued to deepen. It largely plateaued, and fewer comparisons remained significant. The underlying protein changes at the more active doses were mostly sustained or still developing, but the aggregate clock scores stopped falling.

What did the proteins show?

If the clocks merely registered that patients’ lungs were improving, the dose with the best lung response should also have produced the strongest “rejuvenation” signal.

It did not.

The 60 mg once-daily regimen produced the largest improvement in forced vital capacity. The 30 mg twice-daily (so 60mg in total but over time) regimen produced the most consistent multi-clock response. Across the six clocks, change in lung function explained a median of only 6% of the variation in predicted biological-age change.

The researchers then compared the trial’s protein shifts with age-associated protein trajectories in 55,319 UK Biobank participants. Proteins altered by rentosertib were enriched for proteins that normally change with age. More strikingly, changes in the 30 mg twice-daily arm ran modestly but significantly against the direction of normal aging. The 60 mg once-daily arm—again, the best one for lung function—did not show the same relationship.

Forced vital capacity captures only one dimension of IPF. Reducing systemic inflammation or metabolic dysfunction could make an aging clock read younger without changing fundamental aging biology.

It also suggests that aging biomarkers could reveal differences between dosing schedules that a standard disease endpoint misses. Rentosertib has a half-life of roughly 7–11 hours. Two 30 mg doses may maintain steadier exposure, while one 60 mg dose creates a higher peak. Equal daily milligrams do not necessarily mean equal downstream biology.

Looking beneath the clock

Proteomic clocks have one major advantage over many DNA-methylation clocks: their inputs are proteins, the molecules actually executing biological processes. Researchers can inspect which proteins changed and ask what pathways they belong to.

Rentosertib altered the trajectories of 326 proteins across the treatment arms, compared with only two in the placebo group. The changes included lower levels of proteins involved in fibrosis and extracellular-matrix remodeling, such as COL1A1, MMP10 and FAP, and higher levels of proteins involved in metabolism and stress resistance, including NAMPT, SOD2 and ALDH1A1.

The researchers also tested established senescence signatures. In the placebo group, proteins from the SenMayo panel became more abundant over time. Treated groups generally moved in the opposite direction, while a gene set associated with inhibition of senescence moved upward. Proteins including EREG, IGFBP4, MMP10, MMP13 and SPP1 repeatedly contributed to the divergence.

Beyond senescence, the 30 mg twice-daily regimen affected glutathione metabolism, cholesterol metabolism and the pentose-phosphate pathway. The analysis also pointed toward modulation of IGF signaling, growth-factor pathways and nutrient sensing—processes with long-standing connections to aging biology.

All the ways it is “the first time”

What rentosertib appears to be first at is this combination:

1. A new drug, rather than a lifestyle intervention or an already approved medicine repurposed after the fact.

2. A new target selected partly through aging biology, not merely a conventional disease target later rebranded as geroscience.

3. A randomized clinical-trial dataset with longitudinal sampling.

4. A head-to-head analysis using six independently developed proteomic clocks.

5. A multi-layer attempt to separate disease response from aging biology using lung function, normal-aging trajectories, senescence signatures and pathway analysis.

The authors describe this as a blueprint for a dual-purpose clinical trial: treat a specific age-related disease while simultaneously looking for evidence of broader geroprotective activity. That is the right framing.

Importance of including clocks in clinical trials

The longevity field does not mainly suffer from a shortage of molecules that improve a biomarker in mice. It suffers from a translation problem.

Waiting to learn whether a drug extends human lifespan is impossible within a normal development cycle. Even waiting for multiple diseases to appear takes years and enormous trials. Without credible intermediate endpoints, potentially valuable geroprotectors can remain invisible inside conventional drug programs.

Proteomic clocks could become one layer of that intermediate infrastructure. They might help researchers:

• identify disease drugs with broader effects on aging biology;

• compare regimens that look similar on the primary endpoint;

• select candidates for dedicated geroscience trials;

• connect a composite age signal to specific pathways and proteins; and

• build evidence while remaining inside existing regulatory indications.

No clock is ready to serve as a surrogate for longer life or even longer healthspan. For that, changes in the clock must repeatedly predict later changes in function, disease and mortality—and must do so across drugs, populations and laboratories. But biomarkers do not need to be perfect or causal to be useful. They need to be reproducible, technically reliable and predictive of outcomes that matter.

Rentosertib is a valuable stress test of that proposition.

What’s next?

Rentosertib has now entered a larger phase 3 trial in China, designed to test whether its early lung-function result translates into durable clinical benefit. This is the most importants news the longevity ecosystem had since the development of the first aging clock in 2013 - today, we became a milestep closer to a real gerotherapeutic.

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This is a story about the power of A-list celebrities in biotech. If I saw their pitch in my DMs with no mention of Lady Gaga, I would have paid some attention, but with way more reserve, and my first thought would be - ah yes, another biotech - how do you think your approach to longevity is different? But instead, seeing Gaga post about co-founding a longevity biotech, not supplements, not wellness, actual biotech, my mind, for a very joyous 15 minutes, turned back into a fangirl - because what do you mean GAGA is now doing what I do?? Now, that I’ve calmed down, let’s properly examine Outer Bio and it’s potential in the longevity ecosystem

Before we proceed, I highly recommend putting this playlist on

What is Outer Bio?

Founded in 2022. Based near Cambridge, Massachusetts. Nineteen employees and about $23 million raised, according to recent reporting. (TechCrunch, The Next Web)

Lady Gaga—Stefani Germanotta— co-founded Outer and sits on its board. Her fiancé, Michael Polansky, told Rolling Stone that the company was her idea and that they initially kept her involvement private because Outer was a research company, not a consumer-facing brand. (Rolling Stone)

That distinction matters. Gaga is not lending her face to a biotech company after the science has been built. She was involved at the beginning.

Outer is an R&D company. Its plan is to discover bioactive ingredients and work with beauty, personal-care, biotech and pharmaceutical partners. Its central asset is a human-skin experimental platform called Yuna.

Let’s shine a bit of light on the co-founder, Michael Polansky, though. It’s not always easy being so close to such a supernova as Gaga. Even I titled this post as “Gaga’s company” even though she is just a part of a much larger team, without whom Outer would not exist. I wonder if Michael, down deep, feels as if his spothlight is being taken away. On the other hand, would the company manage to attract the attention of more than 1.4M people on X alone in 24 hours, if not for an A-list celebrity?

Is this really the first celebrity-involved longevity company?

No.

Celebrity money entered longevity well before Outer. John Legend, Chrissy Teigen, Pedro Pascal, Kevin Hart, Zac Efron and others invested in David Sinclair’s consumer-longevity company Tally Health in 2023.

But this time, an A-list celebrity, is not just lending their face and brand to the biotech, nor just their money - Gaga IS the co-founder: one of the world’s biggest pop stars quietly co-founding a wet-lab, tissue-based, longevity-adjacent biotechnology company.

What Outer actually does with the skin

Outer receives de-identified, consented skin left over from surgery, often cosmetic procedures, that would otherwise be discarded.

The tissue is already full-thickness human skin. Epidermis. Dermis. Multiple resident cell types. Some immune-associated signalling.

Outer cuts a surgical specimen into biopsies and places each one on a porous, 3D-printed gyroid support at an air–liquid interface. The structure helps nutrients reach the tissue and waste diffuse away. The company says this preserves tissue architecture and measurable biological function for four weeks. One surgical specimen can generate up to 100 biopsies, and Outer says it has collected data across more than 300 donors. (Outer Bio)

The extra time matters. Acute irritation or toxicity can appear within hours or days. Collagen remodelling, sustained inflammation, barrier repair and senescence-associated changes can take weeks.

This gives Outer something much more useful than a single endpoint: a time series of how real human tissue responds, deteriorates and sometimes recovers.

This is ex vivo explant culture. It is not an organoid, a reconstructed skin equivalent, a bioprinted organ or transplantable tissue. “Alive” means the cells remain metabolically active, the tissue architecture is sufficiently preserved and the sample can still mount a measurable response to inflammation, UVB or a drug. It does not mean there is a tiny self-sustaining organ growing in a dish.

Outer is unusually candid about the boundaries. Yuna retains resident immune signalling, but it cannot recruit immune cells from the blood and it has no full vascular perfusion. Glands, hair and neuro-skin biology are still on the roadmap. (Outer Bio)

There are companies that really do grow human tissues from cells. Vivodyne, for example, cultivates self-assembling organ tissues on microfluidic chips and uses robots to perturb and measure them. Even those are miniature experimental tissues, not full-sized replacement organs.

So the honest version is less sci-fi but still interesting: Outer keeps small pieces of donated human skin alive outside the body for four weeks and repeatedly measures how they respond. That is a platform claim. It is not a regenerative-medicine claim.

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Is four-week living skin actually new?

Also not exactly.

Commercial ex vivo skin platforms already exist. Genoskin says its NativeSkin platform remains viable and immunocompetent for up to 10 days. Ten Bio says its mechanically tensioned TenSkin platform remains viable for 14 days. Both use ethically sourced surgical skin and already serve researchers testing drugs, cosmetics, wounds and inflammatory responses. (Genoskin, Ten Bio)

Nor is four weeks without academic precedent. A published 2022 protocol describes maintaining human skin explants for up to four weeks, and older full-skin culture systems have also reported experiments at four weeks. (Journal of Visualized Experiments, Steinstraesser et al.)

What has Yuna actually demonstrated?

Outer has released a bioRxiv preprint describing three validation experiments.

First, it induced a psoriasis-like inflammatory state using IL-17 and IL-22, sustained it for three weeks and then suppressed parts of that response with tofacitinib, a known JAK inhibitor.

Second, it treated skin from donors aged 58–74 with dasatinib or dasatinib plus quercetin. After three weeks, the treated tissue showed reductions in markers including IL-6 and MMP1 compared with vehicle.

Third, it exposed skin to UVB and showed that a topical sunscreen reduced the resulting tissue damage and inflammatory signals. (Preprint, Outer’s summary)

These are sensible validation experiments. Known insults create expected biology. Known interventions move the expected markers in the expected direction.

But they do not show that Outer has discovered a new anti-aging intervention (yet). Tofacitinib is already a drug. Dasatinib and quercetin are among the most frequently studied senolytic combinations. Sunscreen protecting skin from UVB is not a surprise.

What the paper supports is narrower: Yuna can maintain sufficiently responsive human skin to model several chronic processes over weeks. Good first step, keep it like that.

Skin longevity landscape: Outer’s competitors

Costemtic “anti-aging” is a much bigger market than longevity biotechnology. It’s not surprising, since wrinkles are one of the first thing people associate with aging, and (almost) nobody wants to have them. However, Skin longevity, is so much different than what the anti-aging creams try to sell (or used to, as recently the companies began using some promising actives, but it used to be just a nice smelling moisturizer market Now, skin longevity encompasses companies in AI skin analysis, lab-grown tissue, cosmetic ingredient discovery and actual drug development and more. Where does Outer Bio fit?

The measurement layer: Haut.AI

Haut.AI’s software analyses facial images, measures visible skin features and powers personalised recommendations, remote studies and SkinGPT simulations of how skin might age or respond to a product. The company has also worked with major beauty and consumer-health businesses, including Beiersdorf, Ulta Beauty, Givaudan and Noom. They have one of the best perforimg aging clocks ever, judging by mean avarage error: check them out here.

Its raw material is pixels and clinical image data.

Outer looks underneath. Its raw material is living tissue, histology, secreted proteins and gene-expression data. Haut.AI is trying to tell a brand what skin looks like, and what it might look like later, depending on the intervention. Outer is trying to tell a brand what the tissue is doing and which molecule might change it.

That makes the two more complementary than directly competitive. Haut.AI could measure the phenotype in real people. Outer could investigate the mechanism and screen possible interventions before a clinical study begins. And I can’t wait to see that collaboration happen.

The tissue layer: Genoskin, Ten Bio and Vivodyne

If the comparison is Yuna, Outer’s living-skin platform, the closest commercial neighbours are Genoskin and Ten Bio.

Both give pharmaceutical and cosmetics companies access to living human skin for testing. The basic proposition is similar: human tissue can produce more relevant results than a flat layer of cells, without going straight into an animal or human trial.

Outer’s proposed advantage is experimental duration. Yuna is designed to keep donor skin alive for longer, allowing researchers to observe slower processes and repeated treatments rather than a short burst of toxicity or absorption data.

The second difference is data. Outer is not only looking at whether the tissue survives or becomes irritated. It is collecting histology, imaging, secreted proteins and gene-expression data, then using those results to improve its prediction models.

Vivodyne belongs in the same infrastructure category, although its ambitions extend beyond skin. It grows engineered human tissues for drug testing and disease modelling. The difference is that Outer is starting with donor skin and cosmetic bioactives, while Vivodyne is building a broader preclinical tissue platform.

These companies are not necessarily fighting for the same end customer. But they are competing to become the human tissue layer between cell culture and clinical trials.

The discovery layer: Debut

If the comparison is AI-led ingredient discovery, Debut is probably the closest business-model analogue.

Debut combines machine learning, genomics and wet-lab validation to discover skincare ingredients and turn them into formulations. It has also moved further downstream, using its discovery platform to create consumer products.

Outer’s pitch is a tighter closed loop. Predict a compound. Test it in cells. Test it again in long-lived donor skin. Feed the multi-omic results back into the model. Repeat.

In theory, that loop should help Outer identify compounds that work in complex human tissue, not merely in a simplified assay. It could also give the company a proprietary dataset that becomes more valuable with every experiment.

This is probably the most interesting part of the business—and the least proven.

We have not yet seen enough public data to know whether Outer’s system discovers better ingredients than Debut, conventional high-throughput screening or a good team of cosmetic chemists. A sophisticated feedback loop is not automatically a useful one.

The product layer: OneSkin

OneSkin sits further downstream.

It discovered the OS-01 peptide, put it into a consumer product and ran a small 22-person, 12-week, split-face, vehicle-controlled study. The study reported improvements in transepidermal water loss and some wrinkle and texture measures.

The drug layer: Rubedo

Finally, there are companies such as Rubedo Life Sciences, which belongs in a different category altogether.

Rubedo is testing a drug candidate in people for age-related skin pathologies. That means making therapeutic claims and accepting the clinical, regulatory and financial burden that comes with them.

Outer is currently developing cosmetic bioactives.

That distinction matters. “Skin longevity” can describe everything from a moisturiser with a peptide to a drug intended to treat an age-related disease. The science, evidence requirements and potential value of those products are not comparable.

Where Outer fits

The market map, then, looks something like this:

• Haut.AI measures and predicts the visible phenotype.

• Genoskin and Ten Bio preserve donor skin for experiments.

• Vivodyne grows engineered human tissues.

• Debut discovers and commercialises beauty ingredients.

• OneSkin sells a longevity-positioned intervention.

• Rubedo develops an actual drug.

• Outer is trying to connect tissue, data and discovery in one system.

For now, the public evidence mostly supports Yuna as an interesting tissue platform. It does not yet establish that Yuna plus AI is a superior ingredient-discovery engine.

That is the experiment Outer is really running.

What is Outer’s AI ?

This is where the public evidence becomes much thinner.

Outer describes a model trained on its own experimental data that predicts compounds likely to influence particular skin functions. Candidates are filtered computationally, tested in faster cell assays and then validated in Yuna. The result is fed back into the system.

The company says its model can computationally pre-screen approximately 750 million compounds per year. It has also reported six active development programmes, several dozen additional hits and a pace of roughly one new candidate every six weeks. Four of the six leads are reportedly considered likely to reach commercialisation. (Outer Bio, The Next Web).

For now, we have not seen the compound structures, prospective model benchmarks, comparison against standard virtual screening, blinded hit rates, independent replication or human validation of an AI-generated ingredient. The Yuna preprint validates the tissue system using known interventions. It does not validate the AI discovery engine using a novel molecule.

This is the most important distinction in the whole story.

Outer has shown that it can generate interesting biological data. It has not yet publicly shown that its AI converts those data into better products.

Why begin with cosmetics?

Because cosmetics are a much faster place to prove a discovery platform than prescription drugs.

In the US, most cosmetic products and ingredients do not require FDA premarket approval, with the important exception of colour additives. Companies are still responsible for safety, substantiation and compliant labelling, but the route to market is far shorter than the clinical-development path for a new drug. (FDA)

That makes skin bioactives a logical starting point. Outer can discover an ingredient, generate mechanistic and tissue-level evidence, license it to an established brand and potentially reach consumers without building its own distribution network.

And yes, Lady Gaga already owns a beauty brand: Haus Labs.

So, is Outer a longevity biotech?

I would call it longevity-adjacent biotechnology.

Skin aging is real aging. Senescence, extracellular-matrix breakdown, chronic inflammation, impaired repair and barrier dysfunction are legitimate age-associated biological processes. A platform that lets researchers observe them in intact human tissue for longer could help develop genuine geroscience interventions. Outer is still very early, but they claim to have preclinical molecules in the pipeline - whether their molecules will bring us closer to an actual “cure to aging” - I doubt it - but do they have high chances of driving the anti-aging cosmetic industry finally beyond retinoids, peptides or PDRN? I am quite convinced that yes. And if they will spruce up the Haus Labs cosmetics with senolytic or anti-inflamatory molecules, and demonstrate the effectiveness in at least a human observational study, sign me up as a customer.

If Outer can do the above, the celebrity story will become the least interesting part of the company.

Thanks for reading Regeneration.AI. Subscribe for more analysis of longevity, regenerative medicine and the companies trying to turn both into products.

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The 20 finalists reveal a field split between two competing models of longevity medicine:

1. High-technology rejuvenation therapeutics—cell therapies, engineered extracellular vesicles, gene delivery, mitochondrial drugs, targeted biologics and protein degraders.

2. Deployable multidomain programs—combinations of existing drugs, supplements, nutrition, exercise and personalized digital care.

The $1 million Milestone 2 awards strongly favored the first group. At least 6 of the 10 awardees are advanced therapeutic platforms, compared with only approximately 1–2 of the 10 non-awarded finalists. However, the finalist cohort as a whole contains more combination programs than any single therapeutic modality.

1. Judging criteria

Teams were scored from 1 (best) to 9 (worst) across six core criteria:

• Team: Relevant scientific and clinical-trial experience, complementary expertise, effective governance, and capabilities in study coordination, biostatistics, data management, and measurement of muscle, cognitive and immune function.

• Clinical center: Availability of qualified staff, equipment and laboratory infrastructure; access to participants; ability to recruit and retain them; and capacity to follow common protocols and transmit high-quality data securely.

• Scalability and accessibility: Whether the intervention could reach a large population, considering manufacturing and delivery constraints, stability, treatment burden, safety and quality-control risks, and affordability.

• Scientific rationale: The rigor of the underlying research and whether the proposed mechanism and intervention were supported by credible preclinical, clinical or published evidence.

• Preliminary human data: Quality of proof-of-concept results, including safety, adherence, recruitment, data integrity, relevant biomarkers, and evidence of effects across multiple physiological systems.

• Finals testing approach: Feasibility of the proposed one-year trial, including population selection, sample size, dosing, controls, randomization, blinding, recruitment and retention, product availability, safety monitoring, timelines and contingency plans.

Safety, human-subject protections, regulatory readiness and sufficient funding were additionally assessed as acceptable or unacceptable. Judges then assigned a weighted overall score reflecting the likelihood that each intervention could improve muscle, cognitive and immune function; the ten highest-ranked teams received $1 million and automatic advancement. XPRIZE did not publish the final weights, cut-off scores or individual scorecards. Source: XPRIZE Healthspan Finals Application Guidelines

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2. Who was selected—and who actually received money?

XPRIZE announced 20 finalists on August 11, 2026. All 20 advance toward the clinical-trial phase, but only 10 received a Milestone 2 award.

Each Milestone 2 awardee receives:

• $1 million

• Access to centralized clinical-testing resources

• Trial coordination through the University of Utah Data Coordinating Center

• Central laboratory, biomarker and biorepository support coordinated by UC San Diego

The final prize—up to $81 million—is expected in 2030. Finalists must attempt to restore muscle, cognitive and immune function by the equivalent of at least 10 years, ideally 20, in adults aged 50–90, within no more than one year of treatment. XPRIZE’s official announcement

Milestone 2 awardees: $1 million each

Finalists advancing without a Milestone 2 cash award

The official list of all 20 finalists was reported by XPRIZE and independently summarized by Longevity.Technology.

2. Quantitative analysis

The awards favored advanced biotech

The awardees include:

• A monoclonal antibody

• A stem-cell product

• A plasmid gene therapy

• A mitochondrial peptide

• A targeted progerin degrader

• An engineered EV system

• A plant-EV intervention

• Two drug or drug–lifestyle combinations

• One undisclosed epigenetic program

By contrast, most of the non-awarded finalists rely on:

• Exercise and dietary programs

• Existing prescription drugs

• Supplements or food-derived compounds

• AI personalization

• Wearables and behavioral coaching

A lifestyle program may be easier to scale, but a targeted biologic or regenerative therapy may be judged more likely to generate the very large functional effect required by the prize.

4. Geographic trend

• Asia: 11 finalists, 55%

• United States: 9 finalists, 45%

• Europe: 0

• Canada: 0

• Australia: 0

• Latin America, Middle East and Africa: 0

This is striking because the 2025 semifinalist pool contained teams from Europe, Canada, Australia and other regions. None survived into the final 20.

The competitive center of translational longevity has shifted toward an American–East Asian axis. Japan is particularly overrepresented: one-quarter of all finalists come from Japan, despite the country’s smaller biotechnology investment base relative to the US (Longevity Education Hub offers the free, CME accredited course in healthy longevity medicine in japanese!).

5. Dominant biological trend: inflammaging

Inflammation and immune decline are the closest thing to a consensus mechanism in the finalist cohort.

Even teams nominally focused on mitochondria, metabolism, stem cells, exercise or the microbiome usually claim downstream effects on:

• Chronic low-grade inflammation

• NK- and T-cell competence

• Senescent-cell clearance

• Macrophage function

• Tissue repair

• Fibrotic signaling

This likely reflects the design of the competition: every finalist must improve immune function as well as muscle and cognition. Inflammation provides a plausible mechanistic bridge connecting all three.

6. Other major trends

A. Repurposing is highly competitive

Several finalists avoid the conventional decade-long drug-development pathway:

• Rapamycin

• Lamivudine

• GLP-1 agonists

• Elamipretide, already extensively tested clinically

• An antibody repurposed toward inflammaging

  
  XPRIZE’s one-year treatment window and accessibility requirements naturally reward therapies with known safety, manufacturing and human-exposure data.

B. Reprogramming is underrepresented, contrary to the funding hype

The awarded group includes cells, EVs and gene delivery. However, there is no clearly disclosed, conventional OSK/OSKM partial-reprogramming therapy among the finalists. RETRO-EPIGERNA may involve epigenetic regulation, but its intervention remains undisclosed. The visible finalists generally favor:

• Repairing damaged tissue

• Improving mitochondrial function

• Modifying circulating signals

• Removing toxic proteins

• Restoring immune surveillance

rather than directly resetting cell identity.

That suggests XPRIZE selection currently rewards translational readiness over maximal theoretical rejuvenation.

C. EVs have emerged as a real therapeutic category

Two awardees are EV-based:

• Goda Lab’s engineered mammalian small EVs

• TIME TRAVELER’s edible plant-derived EVs

This is notable because they sit at opposite ends of the development spectrum:

• Goda offers targeted, engineered regenerative biotechnology.

• TIME TRAVELER offers potentially inexpensive, orally deployable plant EVs.

If either succeeds, EVs could become one of the most important validated delivery or signaling platforms in longevity medicine.

D. AI is mainly used for personalization—not drug discovery

AI is present in ANI Biome, NUS comercial entity, GOQii and ASU, but primarily for individual stratification, dynamic treatment adjustment, digital phenotyping, wearable-data interpretation or multimodal biomarker integration.

The finalists do not show a strong wave of purely AI-discovered novel geroprotective drugs. AI is functioning as the control layer for combination medicine, not as the therapeutic itself.

E. Functional endpoints are displacing aging clocks

Many teams use epigenetic clocks, multi-omics or biological-age scores as secondary measures. But since the competition is ultimately structured around muscle function, cognitive performance and immune function, atreatment will not win merely by lowering a biological-age estimate. It must make older participants function measurably more like younger people.

XPRIZE is therefore testing a more demanding proposition than most commercial longevity clinics

7. Important absences

The finalist list is as revealing for what is missing as for what is present. There are no clearly visible finalists centered on:

• In-vivo OSK/OSKM reprogramming

• Telomerase gene therapy as the principal intervention

• Plasma dilution or therapeutic plasma exchange

• Organ replacement or engineered organs

• Microbiome transplantation

• CRISPR-based permanent genome editing

Several of these approaches were represented in the broader longevity ecosystem or earlier applicant pool. Their absence likely reflects safety, scalability, clinical readiness or difficulty demonstrating benefits across all three XPRIZE domains within one year.

8. Overall verdict

The finalists do not support the idea that the field has converged on one “best” anti-aging target. Instead, they show convergence at a higher level:

1. Aging must be treated systemically.

2. Advanced biotech is favored for funding, but scalable repurposed interventions remain competitive.

3. The US and East Asia now dominate translational longevity.

4. The eventual winner may be determined as much by trial execution and participant adherence as by mechanism.

XPRIZE finalist lists show two pathways in longevity: one with immediate gragerotherapeutic biotech seeking large biological effects and precision preventive medicine seeking broad accessibility. The clinical phase will reveal whether the prize’s extraordinarily ambitious functional target is better met by a powerful new modality or by a carefully engineered combination of interventions that already exist.

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Recent experiments have now extended both extremes of that timeline.

In vitrification, technique which is promised to allow for indefinite organ biobanking, Dr Brian Wowk, Dr Gregory Fahy and colleagues successfully vitrified, rewarmed and transplanted a 13.9-gram rabbit kidney, establishing the current record for the largest vitrified vital organ returned to clinically normal function. A separate team led by Dr Wei Rao and Dr Jing Liu subsequently demonstrated the first successful allogeneic transplantation of a vitrified rabbit kidney using a liquid-metal-assisted heat-transfer system.

In supercooling, technique that is promised to solve organ waste due to donor-recipeint distance, Dr Matthew Powell-Palm and collaborators have now reported transplantation of pig kidneys after as long as 72 hours of ice-free storage at approximately −4°C, without the use of (toxic) cryoprotectants. This appears to be the longest reported supercooling period for a transplanted kidney and the first demonstration at this duration in a large-animal kidney model.

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Some cryo background, if you’re new here:) (skip if you’re a pro)

Vitrification aims to stop this clock much more completely. Instead of allowing water to organize into damaging ice crystals, an organ is perfused with a concentrated cryoprotective solution and cooled until it enters an amorphous, glass-like state. Unlike conventional freezing, vitrification does not produce an organized crystalline structure that can rupture cells and blood vessels.At sufficiently low temperatures, molecular movement and chemical reactions become extremely slow. A vitrified organ could therefore, in principle, remain stable for months, years or longer without the continuing ischemic deterioration seen during conventional cold storage. The hardest parts are not maintaining the organ at cryogenic temperature, but getting it safely into and back out of the vitrified state.

First, enough cryoprotectant must reach every part of the organ to suppress ice formation. These compounds can themselves cause chemical toxicity, osmotic stress and cellular dehydration, particularly at the high concentrations required for organ vitrification. Cooling must then be fast and uniform enough to prevent ice while avoiding excessive thermal stress. Rewarming may be even more difficult. A solution that vitrified successfully during cooling can still crystallize as it passes back through intermediate temperatures. The organ must therefore be warmed faster than its critical warming rate. At the same time, uneven heating can make the surface and interior expand at different rates, generating enough mechanical stress to crack the vitrified organ.

Traditional warming from the outside becomes progressively less effective as organ size increases. The surface may overheat while the centre remains trapped within the temperature range in which ice can form. This size-dependent rewarming problem is why volumetric approaches—including nanowarming, dielectric heating or liquid-metal-assisted system (latest breakthrough) have become so important. Rather than waiting for heat to diffuse slowly from the surface, these technologies attempt to generate or distribute heat throughout the organ.

Supercooling takes a less extreme approach. The organ is cooled below water’s normal freezing point but remains liquid: it is neither frozen nor converted into a glass. Lowering the temperature further than conventional cold storage suppresses metabolism and slows deterioration, while avoiding the high cryoprotectant concentrations and extreme rewarming requirements associated with vitrification.

The trade-off is that a supercooled organ remains biologically and chemically active. Supercooling can slow biological time for days, but it does not stop it for months or years. The liquid state is also metastable: although no ice is initially present, a microscopic impurity, surface defect or mechanical disturbance can trigger nucleation and rapidly freeze the entire organ. Once ice begins forming, it can cause the same structural damage that supercooling was intended to prevent.

Supercooling has already produced transplantable organs in other models. In 2014, rat livers were preserved in a non-frozen state for up to four days before transplantation, tripling the viable preservation duration in that model. The latest reported pig-kidney experiments are especially relevant because porcine kidneys are much closer to human kidneys in size and surgical anatomy.

The two technologies therefore solve different versions of the same problem. Supercooling could extend today’s transplant window from hours to days, creating more time for transport, matching and surgery. Vitrification aims to make the window effectively open-ended, enabling true organ banking—but requires the organ to survive much more demanding cryoprotectant loading, cooling and rewarming procedures.

The largest vitrified organ successfully transplanted

In May 2025, researchers from 21st Century Medicine published the results of a 55-megahertz dielectric warming system designed to rewarm vitrified organs rapidly and uniformly. Of three rabbit kidneys that were vitrified, dielectrically rewarmed under slightly different conditions and transplanted, one recovered long-term function. The kidney weighed 13.9 grams, approximately an order of magnitude more than the rat kidneys used in the landmark 2023 nanowarming transplantation study.

The recipient’s serum creatinine eventually fell below 2 mg/dL, a level the researchers characterized as clinically normal renal function. The rabbit was still alive 17 months after transplantation when the study was prepared for publication (Wowk et al., 2025). The authors described the kidney as the largest vitrified vital organ successfully returned to clinically normal function to date.

When it comes to rewarming, Wowk’s system generated an oscillating electric field between capacitor plates. Water and cryoprotectant molecules throughout the sample absorbed energy from the field, allowing the kidney to be heated volumetrically rather than relying entirely on conduction from its surface. In physical experiments, the 800-watt system produced peak warming rates close to 200°C per minute in approximately 15-gram rabbit kidneys contained within a total volume of around 45 mL. Computer modelling was used to optimize the capacitor plates, organ container and surrounding dielectric materials to make the internal electric field more uniform.

The experiment established that a rabbit-sized kidney can survive vitrification, rapid dielectric rewarming and transplantation with recovery of clinically normal function.

It did not yet demonstrate that this outcome can be produced consistently. Only one of the three transplanted kidneys achieved long-term recovery.

Wei Rao’s liquid-metal route to rabbit-kidney vitrification

Less than a year later, researchers led by Wei Rao and Jing Liu at the Technical Institute of Physics and Chemistry of the Chinese Academy of Sciences reported another route to vitrifying and transplanting a rabbit kidney.

Published in Matter in March 2026, the study introduced a flexible composite made from a eutectic gallium–indium liquid metal mixed with polyvinylpyrrolidone.

What are liquid metals?

Liquid metals are metals or alloys with melting points near or below room temperature, combining the thermal and electrical conductivity of a metal with the ability to flow and conform to complex shapes. Rao’s team used eutectic gallium–indium—an alloy containing approximately 75% gallium and 25% indium—mixed with polyvinylpyrrolidone to create a flexible heat-transfer composite. Beyond cryopreservation, gallium-based liquid metals are being explored in stretchable circuits, wearable sensors, neural interfaces, soft heaters and robotics, while nanoscale formulations have been investigated for drug delivery, medical imaging and cancer treatment although most biomedical applications remain experimental rather than clinically validated (but check out Dr Rao’s papers because the POCs are fantastic! I pulled an all-nighter reading them - couldn’t stop.

The video above is taken directly from Dr Rao’s paper. It shows step by step how the experiment was conducted. It is my first time seeing such a video in a paper and I LOVE IT! It’s such a good way to engage with a reader and let them immediately grasp the gist before getting into the details - can more of us do it, please?

The material was placed around the rabbit kidney, where it closely followed the organ’s irregular surface, and introduced into its vascular network. The external layer conducted heat into the organ while the intravascular material generated heat under an electromagnetic field, allowing the kidney to warm from both outside and within and reducing the temperature gradients that can cause ice formation or cracking. A gelatin transition layer enabled the material to be removed and recycled after rewarming. Importantly, the liquid metal did not replace conventional vitrification cryoprotectants; it acted primarily as a high-conductivity rewarming system. The liquid metal raises conductivity, reduces contact resistance and improves heat distribution. The organ must still be placed in conditions that prevent ice formation during cooling and rewarming i.a use cryoprotectants like DMSO, propylene glycol, trehalose etc.

The proposed advantage is straightforward: instead of allowing heat to travel slowly through poorly conductive biological tissue, the liquid metal creates what the authors describe as a thermal highway around and through the organ. The material had a reported thermal conductivity of 9.3 W/m·K, approximately 10.3 times greater than that of the iron-oxide-containing cryoprotectant formulation used as a nanowarming comparator. Because the flexible material conformed closely to the organ surface, it also reduced the insulating gaps and interfacial resistance that can occur when a soft, irregular organ is placed against a rigid warming material.

Across the tissue experiments, the system reduced maximum surface-temperature differences by between 10°C and 41.9°C and lowered calculated thermal stress by approximately two orders of magnitude. Compared with water-bath controls, post-rewarming viability increased 1.7-fold in rabbit skin and 3.6-fold in arteries.

The vitrified and rewarmed kidneys maintained sufficient morphology and function to enable the first successful allogeneic transplantation of a vitrified rabbit kidney, with the graft recovering enough renal function to support the recipient’s survival.

The Rao platform may also be more adaptable to organs with complex or irregular geometries because the heat-transfer material can conform to the surface and use vascular channels to distribute heat internally.

Supercooling record: time + size + transplant

In January 2026, a peer-reviewed study published in the American Journal of Transplantation in 2026 provided the first major large-animal evidence. Calderon Novoa and colleagues preserved pig kidneys for five hours or for prolonged periods of 24 to 48 hours at subzero, nonfreezing temperatures and subsequently assessed them using porcine autotransplantation. The study concluded that subzero kidney preservation was feasible and could be followed by transplantation, although the authors emphasized that the protocols still required optimization. However, the University of Toronto group didn’t get much time to enjoy their record-bearing title, because just 5 months later, in July 2026, Dr Matthew Powell-Palm and collaborators have now reportedly extended supercooled pig-kidney preservation followed by transplantation to 72 hours.

This work is based on isochoric supercooling, meaning that the preservation solution and biological sample are enclosed within a rigid chamber at constant preassure. The kidneys were maintained at approximately −4°C without ice formation and without the concentrated permeating cryoprotectants used in vitrification. Experimental groups reportedly included kidneys stored for 24, 48 and 72 hours before being transplanted back into pigs.

According to reporting on the study, the 72-hour grafts reperfused after transplantation and recovered renal function during a 30-day observation period. The young pigs continued growing, while the transplanted kidneys enlarged as they compensated for both the animals’ growth and the absence of a second functioning kidney. Can’t wait for the full paper to be published!

Conclusion: A global and increasingly commercial race

1. The large-organ cryo world is no longer USA-centric

   Dr Rao’s achievement is a clear signal that China is not being left behind in the race to bank organs. Her result emerged from the Chinese Academy of Sciences’ Liquid Metal and Cryogenic Biomedicine Research Center, supported by a growing pipeline of government-backed work: Dr Rao now leads more than 20 projects, including a 2024–2029 CAS strategic project specifically focused on temperature control for organ cryopreservation and a separate program aimed at commercializing organ-perfusion equipment. Her team has already developed a domestically designed multi-organ perfusion platform spanning temperatures from approximately 37°C to −10°C. Nor is this an isolated laboratory. China has long-running cryobiology programs at institutions including the Shanghai University of Science and Technology’s Institute of Biothermal Systems (currently led by Dr Yi Xu) —whose roots extend back to 1984—and the University of Science and Technology of China’s Intelligent Cryogenic Biomedical Engineering Laboratory. The Society of Cryobiology’s current president, Dr Xiaoming He, leads his own cryo lab at Tsinghua International Graduate School in Shenzhen. And there are ~many~more. The liquid-metal kidney study should therefore be read not simply as one remarkable paper, but as evidence that sustained institutional funding, specialized engineering infrastructure and a growing domestic research network are beginning to translate into landmark organ-preservation results.

   My bet is that organ and whole-organism cryobiology will enter China’s upcoming or next 5-year-plan. When China designated BCI as a strategic future industry, the field rapidly gained coordinated funding, clinical programs, standards, industrial clusters and state-backed companies, and now there is no doubt that China leads the industry. Cryobiology could follow the same path: shared large-animal facilities, domestic perfusion and rewarming platforms, dedicated translational grants and faster commercialization.

2. Cryo industralization and race towards an integrated platform

   Dr Powell-Palm’s work points toward an equally important commercialization story in the United States. He co-founded BioChoric in 2021 with UC Berkeley professor Boris Rubinsky to translate isochoric supercooling into practical preservation systems, and now serves as President of the newer biostasis venture Maximize Bio. So it’s quite obvious that his research is gearing up to become major competition to established organ-preservation businesses such as TransMedics and XVIVO (read more about them in this regeneration.ai post ). If Maximize Bio can reproduce 72-hour preservation reliably, scale the device across organs and demonstrate clinical safety, the competitive boundaries could change quickly: preservation would no longer require keeping an organ continuously “alive” on an expensive machine. The bigger conclusion is that organ preservation is becoming a platform industry. The likely winners may not be companies committed to one temperature or one device, but those capable of moving organs safely across the full spectrum from perfusion, through supercooling, to eventual vitrification and true organ banking.

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This review covers announcements made between January 1 and July 19, 2026. I know, I know - July is officially H2, but too many cool things happened not to include them!

Disclaimer: This article reflects my personal analysis and opinions only. It does not represent the views, investment positions, recommendations or policies of Qiming Venture Partners, its affiliates, partners, employees or portfolio companies.

The article is provided solely for informational and educational purposes and does not constitute investment, financial, legal, tax, medical or other professional advice, an offer to sell, or a solicitation to buy any security or financial instrument. References to companies, financings, valuations, clinical programs and market opportunities should not be interpreted as endorsements or investment recommendations.

🔥ARDD conference opened registration for 2026

The most elite, largest, validated, GOAT event in longevity — Aging Research and Drug Discovery Meeting - opened registration for its 13 annual meeting in 2026, scheduled for October 1–3 at the David Rubenstein Treehouse at Harvard University. This year the conference focuses heavily on longevity therapeutics and their translation to the clinic, featureing speakers like Ruth Gimeno — Vice President, Eli Lilly, Christophe Weber — Former CEO of Takeda, Elcin Barker Ergun — CEO, Menarini Group ,Ariel Feldstein — Chief Scientific Officer, Pfizer Fiona H. Marshall — President, Novartis, George Church — Harvard University or Alex Zhavoronkov — CEO, Insilico Medicine. The agenda includes Clinical Development Day and the Longevity Medicine Track on October 1, the AI in Drug Discovery Track on October 2 and the Future Technology Track on October 3.

The chairs are the creme de la creme of longevity: Vadim Gladyshev, Jesse Poganik Alex Zhavoronkov, Morten Scheibye-Knudsen, Daniela Bakula, Evelyne Bischof Maximilian Unfried.

The deal is simple - if you are not there, or at least not attending virtually, you are not a serious longevity player.

And now, let’s get to the “meat” of this post - updates from longevity biotech companies:

1. Insilico Medicine

It’s hard to imagine a better BD streak than Insilico Medicine is having in H1 2026. The company just went public on Hong Kong stock exchange at the end of 2025, and managed to move the world’s fist AI designed drug to phase 3 trials, sign over 7.5B USD worth of deals with big pharma, land a Tencent collaboration and much more. Here is a detailed breakdown:

• Eli Lilly 2.75B deal (March 29, 2026) Insilico announced a global research-and-development collaboration with Eli Lilly. Insilico received $115 million upfront, while development, regulatory and commercial milestones could bring the total potential value to approximately $2.75 billion, plus royalties. Lilly obtained exclusive worldwide rights to selected preclinical therapeutic programs and additional candidates arising from the collaboration.

• Longevity board: On April 21, 2026, Insilico Medicine announced what it called the industry’s first Longevity Board to accelerate AI-driven aging research for drug discovery. Chaired by Eli Lilly’s Andrew Adams, the board is intended to guide work in life models, biomarkers of aging, dual-purpose aging-and-disease targets, and clinical development that validates therapeutic effects on hallmarks of aging using biomarkers and foundation models.

• Bora Pharmaceuticals proposed end-to-end alliance potentially exceeding $2.5 billion

  July 14, 2026: Insilico Medicine and Bora Pharmaceuticals announced a proposed multi-target strategic alliance connecting Insilico’s AI-enabled drug-discovery platform with Bora’s development, manufacturing, quality and commercialization infrastructure.

• SK Biopharmaceuticals neuroimmune and CNS discovery alliance valued at more than $2.5 billion

  June 21, 2026: Insilico Medicine and SK Biopharmaceuticals announced a multi-program drug-discovery collaboration covering neuroinflammatory, neurodegenerative and rare neurological disorders. Insilico will apply its AI platform to early discovery, while SK Biopharmaceuticals will lead later-stage development and commercialization.

  The agreement includes up to $18 million in upfront and near-term payments and more than $2.5 billion in total potential consideration, together with single-digit royalties.

• Liquid AI: scientific foundation-model collaboration Insilico Medicine and Liquid AI collaborated through the MMAI Gym model-training infrastructure to develop scientific foundation models.

  Commercial terms were not disclosed.

• Human Longevity Inc Foundation Model collaboration: Insilico and Human Life Foundation Models, a newly established company originating from Human Longevity Inc., announced a multi-year, multimillion-dollar collaboration. Human Life Foundation Models contributes de-identified longitudinal clinical, genomic and imaging data, while Insilico contributes its AI infrastructure.

• Takeda: In July, Insilico added Takeda as another pharmaceutical partner. The agreement includes approximately $60 million in initiation payments, near-term payments and milestones, with total potential value of around $600 million plus royalties.

• Tencent Health — strategic partnership to develop and commercialize specialized AI models for life sciences

  July 20, 2026: During the 2026 World Artificial Intelligence Conference, Insilico Medicine and Tencent Health announced a strategic collaboration covering the training of specialized life-science models, high-performance computing, cloud deployment and commercial distribution. The companies will combine Insilico’s drug-discovery data, scientific-model training experience and MMAI Gym for Science platform with Tencent Health’s medical AI models, cloud-computing infrastructure and enterprise services.

• Servier: multi-program oncology partnership valued at up to $888 million

  January 4, 2026: Insilico Medicine and Servier announced a multi-year, multi-program oncology drug-discovery and development collaboration. Insilico will lead AI-enabled discovery using its Pharma.AI platform, while the companies will share research and development costs. Servier will lead clinical development and worldwide commercialization of resulting programs.

  The agreement provides Insilico with up to $32 million in upfront and near-term research payments and as much as $888 million in total potential payments.

  Believe it or not, but there are actually more deals Insilico made in H1 2026 such as with Hygtia Therapeutics about NLRP3, Ribo Life Science on RNA therapeutics, ASKA Pharmaceutical on women’s health, Tigermed on clinical development, Qilu Pharmaceutical on AI-enabled cardiometabolic targets, China Medical System on CNS autoimmune targets, and more! Wow, wow and just wow.

2. Life Biosciences — partial epigenetic reprogramming reached human clinical testing

• FDA clearance for IND (January 28th): Life Biosciences (THE company people associate with reprogramming, co-founded by Longevity Superstar Dr David Sinclair) received FDA clearance for its IND application for ER-100, a partial epigenetic reprogramming therapy for optic neuropathies. The company described the event as the first FDA-cleared human clinical program using partial epigenetic reprogramming/cellular rejuvenation. ER-100 is based on controlled expression of three Yamanaka factors, OCT4, SOX2, and KLF4, delivered locally to the eye, with the Phase 1 study designed for patients with open-angle glaucoma and non-arteritic anterior ischemic optic neuropathy.

• Series D (April 8, 2026): $80 million to support the ER-100 Phase 1 trial and advance the company’s broader Partial Epigenetic Reprogramming platform. The financing was positioned as providing runway into the second half of 2027. The investors were not discosed.

• First ever human clinical trail for partial reprogramming: On June 9 2026, Life Biosciences announced that the first participant had been dosed in the Phase 1 ER-100 trial in open-angle glaucoma and non-arteritic anterior ischemic optic neuropathy.

This is the cleanest “hardcore longevity to clinic” story of H1 2026. The company is not asking regulators to approve “aging reversal.”, despite how badly the longevity community wants to call it. It is entering through an organ-specific, high-unmet-need indication where local delivery, visual endpoints, and retinal ganglion cell biology make the risk–benefit argument more concrete. The important point is that this is not proof that partial reprogramming works in humans “on aging” ; it is proof that the FDA is willing to evaluate controlled reprogramming when it is packaged as a disease-specific therapy with accepted clinical endpoints.

3. Retro Biosciences

• Initial close of the next financing round (May 22, 2026): STAT reported that the latest fundraising valued the company at approximately $1.8 billion pre-money. The round was led by 4P Capital, but Retro did not disclose the total amount raised or the full investor syndicate in the announcement.

• First pre-print: So far, Retro Biosciences did not share much details about the specifics of their pipeline. That changed in July 2026 with the company’s first official preprint. The paper’s novelty is showing that transgene-free human iPSC-derived hematopoietic stem cells can combine durable adult-like function with sustained molecular youth. Using cells from multiple adult donors, including people aged 57–60, the authors demonstrated robust multilineage engraftment in mice, maintenance of a phenotypic stem-cell compartment, and successful secondary transplantation—evidence of long-term self-renewal rather than transient progenitor activity. At the same time, the grafts retained very young epigenetic ages, longer telomeres with far fewer critically short telomeres, and low age-associated methylation drift, even after roughly ten months of serial in-vivo proliferation. They also showed that HSC identity continued to mature toward a primary adult HSC-like state after transplantation without reverting to the donor’s biological age, supporting the idea that functional maturation and epigenetic aging can be separated. Good preclinical work!

4. NewLimit — $435 million and a promised 2027 human trial

June 2, 2026: NewLimit announced the closing of a $435 million Series C led by Founders Fund, with participation from Thrive Capital, Greenoaks, Quiet Capital, Kleiner Perkins, Eli Lilly Ventures and others. The company said it planned to bring its first epigenetic-reprogramming medicine into human trials in 2027.

Source: NewLimit: $435 million Series C, June 2, 2026

July 10, 2026: NewLimit published a progress update reporting more than 120-fold manufacturing scale-up of its lead program and additional reprogramming payloads in hepatocytes and endothelial cells. These remain internal, company-reported preclinical results.

Source: NewLimit: May–June progress update, July 10, 2026

5. Junevity — Lilly entered transcription-factor resetting

January 12, 2026: Junevity announced the first peer-reviewed publication from its founders showing that repression of individual transcriptional regulators could restore aspects of tissue-repair biology in aged experimental systems.

Source: Junevity: Peer-reviewed cellular-reprogramming research, January 12, 2026

June 2, 2026: Junevity announced a Catalyze Agreement with Eli Lilly ExploR&D to use its RESET platform to discover novel siRNA targets for Parkinson’s disease.

Source: Junevity announcement: Eli Lilly ExploR&D collaboration, June 2, 2026

This may be one of the more sensible approaches hiding under the wide umbrella of “reprogramming.” Instead of resetting a cell through a powerful and pleiotropic Yamanaka-factor system (or their engineered versions), Junevity is trying to identify narrower transcriptional control points that move a diseased cell toward a healthier state. The Lilly agreement is early and has no disclosed economics. But it provides external validation that the platform may generate targets interesting enough for pharma to investigate.

6. Juvena Therapeutics — regenerative biologics received another $33.5 million

January 12, 2026: Juvena Therapeutics announced a $33.5 million Series B led by Bison Ventures to advance its regenerative-biologics pipeline.

Source: Juvena Therapeutics: $33.5 million Series B, January 12, 2026

Juvena is an interesting bridge between regenerative medicine and conventional biologic development. Instead of administering poorly characterized cell preparations and hoping something regenerative happens, it is trying to identify specific proteins responsible for the beneficial effects of stem-cell secretomes and convert them into standardized pharmaceutical products.

7. Cambrian Bio — government capital and human metabolic data

February 24, 2026: Cambrian announced an award of up to $30.8 million through ARPA-H’s PROSPR program to advance its TORnado platform of selective mTORC1 inhibitors intended to improve intrinsic capacity in older people.

Source: Cambrian Bio: ARPA-H award of up to $30.8 million, February 24, 2026

June 18, 2026: Cambrian reported Phase 1b data for ATX-304 in 23 adults with obesity and prediabetes. The company reported statistically significant changes in liver fat, visceral adipose tissue, triglycerides, adiponectin and resting metabolic rate, with an overall tolerability profile comparable with placebo. Two Phase 2 studies are planned.

Source: Cambrian Bio: ATX-304 Phase 1b results, June 18, 2026

Cambrian is now a better example of “aging biology translated through normal medicine” than of a broad longevity holding company. ATX-304 is entering an extremely competitive obesity market, but it is differentiated from appetite-suppressing incretins by attempting to increase energy expenditure and improve metabolic flexibility. The ARPA-H award is also strategically important. The agency is explicitly funding an intervention aimed at intrinsic capacity in older adults, which is much closer to a healthspan endpoint than most conventional disease programs.

8. Calico — the supposedly unknowable pipeline became less unknowable

May 21, 2026: Calico and Nexo Therapeutics announced a multi-target collaboration to discover and develop small-molecule therapies for age-related diseases.

Source: Calico: Collaboration with Nexo Therapeutics, May 21, 2026

June 23, 2026: Calico announced that the FDA had granted Breakthrough Therapy Designation to fosigotifator for vanishing white matter disease. The asset is being evaluated in a Phase 1b/2 program.

Source: Calico: FDA Breakthrough Therapy Designation for fosigotifator, June 23, 2026

9. Juvenescence — Phase 1 completed, efficacy still unanswered

February 26, 2026: Juvenescence announced completion of the randomized, placebo-controlled Phase 1 trial of MDI-2517, its small-molecule PAI-1 inhibitor. The company reported favorable safety and tolerability and a pharmacokinetic profile compatible with once-daily dosing.

Source: Juvenescence: Completion of the MDI-2517 Phase 1 trial, February 26, 2026

PAI-1 sits at the intersection of inflammation, fibrosis, metabolism and aging biology, giving Juvenescence multiple possible indications.

10. BioAge Labs — the post-failure rerating became an NLRP3 story

January 21, 2026: BioAge announced the pricing of an upsized public offering expected to generate approximately $115 million in gross proceeds.

Source: BioAge Labs: Pricing of $115 million public offering, January 21, 2026

April 21, 2026: BioAge reported Phase 1 data for BGE-102, an orally available, brain-penetrant NLRP3 inhibitor. In participants with obesity and elevated inflammation, the company reported large reductions in hsCRP, IL-6 and fibrinogen, with no serious adverse events or treatment-related discontinuations.

Source: BioAge Labs: BGE-102 Phase 1 results, April 21, 2026

May 8, 2026: BioAge reported $384.9 million in cash, cash equivalents and marketable securities as of March 31, with projected runway through 2029.

Source: BioAge Labs: Q1 2026 results and business update, May 8, 2026

June 16, 2026: BioAge announced that the first participant had been dosed in QUELL-CV, a Phase 2 dose-ranging trial of BGE-102 in approximately 160 adults with obesity, systemic inflammation and additional cardiovascular risk factors.

Source: BioAge Labs: First participant dosed in QUELL-CV, June 16, 2026

All the success cases above contributed to BioAge fully rebouncing their stock price from phase-2-failure related drop - great job and a hope story for many other biotechs.

11. Rubedo Life Sciences — senolytics finally produced an early human signal

March 26, 2026: Rubedo announced preliminary results from its European Phase 1 trial of topical RLS-1496 in plaque psoriasis, atopic dermatitis and photo-aged skin. The trial met its primary safety endpoint, and the company reported early target-engagement and clinical signals.

Source: Business Wire: Rubedo RLS-1496 Phase 1 results, March 26, 2026

May 28, 2026: Rubedo announced preliminary Phase 1b/2a results in actinic keratosis. In the first 18 of 24 evaluated patients, the company reported a 46% reduction in lesion count after four weeks, compared with an 11% reduction in untreated control areas, with no serious adverse events or treatment discontinuations.

Source: Business Wire: Rubedo actinic-keratosis Phase 1b/2a results, May 28, 2026

Senolytics have generated years of impressive animal data, failed program (RIP Unity) and an enormous supplement market, but very little convincing human therapeutic evidence. Rubedo’s findings are preliminary and come from small dermatological studies. They do not show that clearing senescent cells extends lifespan, treats systemic aging or works in every disease with a senescence signature. But this is among the first human evidence suggesting that a more targeted senotherapeutic strategy may produce measurable target engagement and a clinical effect. And let’s not foget how huge is the “anti-aging skincare” market.

12. Cyclarity Therapeutics — oxidized cholesterol came out in the urine

May 14, 2026: Cyclarity announced first-in-human data for UDP-003, its engineered cyclodextrin designed to bind and remove 7-ketocholesterol. The Phase 1 study showed no serious adverse events, predictable pharmacokinetics and dose-dependent urinary excretion of the targeted oxidized cholesterol.

Source: Cyclarity: First clinical UDP-003 data, May 14, 2026

It is not evidence of plaque regression. It is definitely not evidence of fewer heart attacks or strokes. The next challenge is showing that removing 7-ketocholesterol meaningfully changes atherosclerotic disease in patients. Still, compared with another preclinical plaque image in a mouse, seeing the targeted damage product leave the human body is real progress.

13. Repair Biotechnologies — the FDA opened a potentially shorter rare-disease route

May 12, 2026: Repair Biotechnologies announced that the FDA had accepted REP-0003 into the Rare Disease Evidence Principles process for homozygous familial hypercholesterolemia.

Source: Repair Biotechnologies: RDEP eligibility for REP-0003, May 12, 2026

The rare-disease entry through homozygous familial hypercholesterolemia is strategically smart. It provides a severe, genetically defined population with accelerated plaque accumulation and enormous unmet need. If REP-0003 can show meaningful plaque regression there, Repair may later have a foundation for broader cardiovascular development.

14. Longeveron — frailty returned as a legitimate clinical endpoint

February 25, 2026: Longeveron announced publication in Cell Stem Cell of Phase 2b results for laromestrocel in age-related clinical frailty. The company reported improvement in physical condition nine months after treatment compared with placebo.

Source: Longeveron: Phase 2b frailty results published, February 25, 2026

May 13, 2026: Longeveron’s first-quarter update reiterated development programs for laromestrocel in frailty, Alzheimer’s disease, hypoplastic left heart syndrome and pediatric dilated cardiomyopathy.

Source: Longeveron: Q1 2026 business update, May 13, 2026

Frailty is one of the most clinically meaningful manifestations of aging and one of the hardest to commercialize. It is heterogeneous, multisystemic and highly sensitive to endpoint selection, background care and patient motivation. That makes positive randomized data important, but it also makes replication and a clear regulatory pathway essential.

15. Vandria — mitophagy produced measurable human pharmacology

July 13, 2026: Vandria announced additional Phase 1 data for VNA-318, its brain-penetrant mitophagy inducer. The company reported drug exposure in cerebrospinal fluid, quantitative-EEG changes and peripheral metabolic biomarker changes consistent with its proposed mechanism.

Source: Vandria: Additional VNA-318 Phase 1 data, July 13, 2026

These are pharmacodynamic data in healthy volunteers, not evidence that VNA-318 improves cognition or slows Alzheimer’s disease. However, CNS penetration plus a measurable effect in the human brain is exactly what an early trial should establish. Vandria now has a stronger translational package for deciding whether the biology survives contact with patients.

16. Gero — a real $17 million financing, plus prestige

June 10, 2026: Gero announced that it had been selected as a World Economic Forum 2026 Technology Pioneer.

Source: Business Wire: Gero named a WEF Technology Pioneer, June 10, 2026

June 17, 2026: Gero announced $17 million in new financing, bringing its total equity funding to $34 million. The company said the proceeds would support preclinical development and expansion of pharmaceutical partnerships.

Source: Business Wire: Gero raises $17 million, June 17, 2026

Gero has credible pharma relationships. The public still has limited visibility into which targets, modalities and programs are becoming proprietary clinical assets. At some point, “the physics of aging” needs to resolve into a development candidate.

17. Genflow Biosciences — several steps toward partnerships, but not a disclosed commercial deal

April 13, 2026: Genflow announced international patent publication expanding protection around its SIRT6-based muscular-disease program.

Source: Genflow Biosciences RNS archive: Patent publication, April 13, 2026

April 20, 2026: Genflow announced a strategic technology collaboration with Acuitas Therapeutics, providing access to Acuitas’s lipid-nanoparticle delivery platform.

Source: Genflow Biosciences: Acuitas collaboration announcement, April 20, 2026

April 28, 2026: Genflow announced that additional Tier-1 animal-health companies had entered confidentiality agreements to evaluate data from its canine SIRT6 gene-therapy program.

Source: Genflow Biosciences: Expansion of animal-health confidentiality agreements, April 28, 2026

18. Loyal — pet longevity raised another $100 million

January 13, 2026: Loyal announced that the FDA Center for Veterinary Medicine had accepted the Target Animal Safety technical section of the expanded conditional-approval application for LOY-002.

This was a safety-section milestone. It was not the Reasonable Expectation of Effectiveness milestone, which had been announced in 2025.

Source: Loyal: FDA acceptance of the LOY-002 Target Animal Safety section, January 13, 2026

February 11, 2026: Loyal announced a $100 million Series C led by age1, with participation from Baillie Gifford and existing investors, bringing total capital raised to more than $250 million.

Source: Loyal: $100 million Series C, February 11, 2026

I was originally hesitant about including Loyal because dogs respond differently from humans to many therapeutics. But if the scientist in me shuts up for a moment, pet longevity is a beautiful market entry. It creates a faster regulatory pathway, emotionally engaged customers, measurable lifespan outcomes and the possibility of making lifespan-extension medicine feel normal before anyone tries to sell it for humans.

LOY-002’s molecular target remains undisclosed, which makes scientific diligence difficult. Commercially, however, Loyal has built the most regulator-legible longevity product in the field.

19. Rejuvenate Bio — Merck Animal Health validated the animal-first gene-therapy strategy

June 8, 2026: Rejuvenate Bio announced a $6 million financing led by VCapital, with participation from Merck Animal Health and others. It also announced a strategic R&D collaboration with Merck Animal Health around a new veterinary gene-therapy program.

Source: Rejuvenate Bio: $6 million financing and Merck collaboration, June 8, 2026

The financing is small relative to Loyal, but Merck’s participation is strategically more important than the dollar amount. Rejuvenate Bio’s human pipeline remains preclinical. For now, veterinary medicine offers the company a more realistic path to product development, commercial partnerships and in-species efficacy data.

20. Mighty Therapeutics — Stealth changed its name after becoming commercial

The first correction is simple: Stealth BioTherapeutics and Mighty Therapeutics are not two separate companies.

January 6, 2026: Stealth announced that Forzinity, its FDA-approved elamipretide product for Barth syndrome, had become commercially available in the United States and outlined its development priorities for 2026.

Source: Stealth BioTherapeutics: Commercial and pipeline update, January 6, 2026

April 30, 2026: Stealth reported that 33 patients had initiated therapy, 85% had obtained full coverage and the first site had been initiated for its required Phase 4 confirmatory trial.

Source: Stealth BioTherapeutics: Forzinity launch update, April 30, 2026

June 16, 2026: The company formally changed its name from Stealth BioTherapeutics to Mighty Therapeutics.

Source: Mighty Therapeutics: Company-name change, June 16, 2026

This is the only company in the deck with an FDA-approved mitochondria-targeted product, although the indication is an ultra-rare genetic mitochondrial disease rather than aging (since the initial trial for aging failed in most of it’s endpoints). That does not prove mitochondrial medicines will treat ordinary aging, but it gives the field regulatory, manufacturing and commercial infrastructure that did not previously exist.

21. L-Nutra — fasting-mimicking nutrition attracted Mubadala

January 21, 2026: L-Nutra announced a $36.5 million investment from Mubadala, bringing total Series D proceeds to $83.5 million.

Source: L-Nutra: Mubadala investment, January 21, 2026

L-Nutra is not a moonshot rejuvenation biotech, but it matters because longevity is also being institutionalized through products closer to preventive medicine, nutrition and consumer-health infrastructure, and bringing serious investor’s like Mubadala gives stong “pro-longevity” market signal.

22. Corsera Health — cardiovascular prevention was reframed as healthspan extension

January 7, 2026: Corsera Health announced an oversubscribed $80 million Series A co-led by Forbion and Population Health Partners. The company also announced that it had initiated dosing in a Phase 1 trial of COR-1004, a subcutaneously administered siRNA targeting PCSK9.

Source: Corsera Health: $80 million Series A and first COR-1004 dosing, January 7, 2026

PCSK9 and angiotensinogen are clinically legible targets. Cardiovascular disease is already an accepted prevention market. The novel part is connecting long-duration therapeutics, lifetime-risk modelling and healthspan economics into one product architecture.

23. Tally Health and TruDiagnostic — biological-age testing began to consolidate

April 29, 2026: Infinite Epigenetics, the parent company of TruDiagnostic, announced the acquisition of Tally Health. Tally is expected to remain a standalone consumer brand while its platform and methylation data are combined with TruDiagnostic’s laboratory and clinical-research infrastructure.

Source: Infinite Epigenetics: Acquisition of Tally Health, April 29, 2026

24. Niagen Bioscience — ChromaDex moved from supplements toward clinical distribution and drug development

February 26, 2026: Niagen Bioscience announced the sale of its non-core reference-standards business to LGC, allowing the company to focus more narrowly on its nicotinamide-riboside platform.

Source: Niagen Bioscience: Sale of reference-standards business, February 26, 2026

May 4, 2026: Niagen launched a clinician-directed telehealth platform offering access to at-home subcutaneous NR injections for eligible patients.

Source: Niagen Bioscience: Niagen Plus telehealth and injection platform, May 4, 2026

July 8, 2026: Niagen announced its first formal pharmaceutical-development program. NB4168 is a proprietary oral molecule intended to produce greater NR exposure, with ataxia telangiectasia selected as the first indication.

Source: Niagen Bioscience: Launch of the NB4168 pharmaceutical program, July 8, 2026

Niagen is no longer just a supplement company. It is attempting to build three businesses from one molecular family: consumer supplements, clinician-distributed compounded products and regulated pharmaceuticals. That strategy creates several revenue channels but also significant regulatory and reputational complexity. A compounded prescription injection is not the same thing as an FDA-approved drug. NB4168 is the program that will determine whether Niagen can cross from NAD-product commercialization into real pharmaceutical development.

25. Function Health — biomarker testing acquired a supplement-data layer

May 12, 2026: Function Health announced the acquisition of SuppCo, a platform for organizing supplement routines and evaluating products.

Source: Function Health: Acquisition of SuppCo, May 12, 2026

Function already owns longitudinal blood-testing relationships and is expanding into MRI and CT. SuppCo adds a data and user-behavior layer around one of the first things longevity consumers do after receiving test results: buy supplements. The scientific risk is obvious. Linking supplement routines to biomarker changes can generate useful hypotheses, but observational correlations inside a commercial platform can very easily become personalized-looking recommendations unsupported by causal evidence.

26. NOVOS Labs — a supplement company produced randomized human data, with caveats

February 19, 2026: NOVOS announced results from a six-month randomized, double-blind, placebo-controlled trial of NOVOS Core in adults over 40. The company reported improvements in flow-mediated dilation, pulse-wave velocity and systolic blood pressure compared with placebo.

Source: NOVOS: NOVOS Core clinical-trial announcement, February 19, 2026

The study did not test cardiovascular events, disability, lifespan or clinical disease outcomes. The results were released by the company, and I have not located a full peer-reviewed publication of the complete trial as of July 19. Still, running a controlled human study on a multi-ingredient longevity supplement is better than assuming that ingredients with separate mechanistic rationales will magically remain effective when placed into one sachet.

27. Rejuvant — an interesting association was marketed as much more than an association

May 21, 2026: Aging Cell published a cross-sectional analysis of 4,260 health enthusiasts who had purchased epigenetic tests and completed lifestyle and supplement questionnaires. Rejuvant use was associated with an average 1.8-year lower epigenetic-age residual in adjusted models.

Source: Aging Cell: Supplement use and epigenetic-age analysis, first published May 21, 2026

28. Mitrix Bio — “full-body mitochondrial transplantation” moved into humans without a conventional clinical-development package

April 6, 2026: Mitrix announced what it described as the first human safety studies of full-body mitochondrial transplantation. The announcement described two older participants receiving escalating mitochondrial infusions.

Source: Mitrix Bio: Human mitochondrial-transplantation safety-study announcement, April 6, 2026

April 6, 2026: Mitrix separately announced the opening of affiliated clinics in California, Texas and Florida offering access to experimental mitochondrial interventions. Its own announcement described the procedure as unproven and experimental.

Source: Mitrix Bio: Clinic-launch announcement, April 6, 2026

29. Revel Pharmaceuticals — going out of Stealth

July 14, 2026: Revel Pharmaceuticals in collaboration with Calico published research describing CMLase, an engineered enzyme designed to remove Nε-carboxymethyl-lysine, or CML, from damaged proteins. In ex-vivo tissue experiments, the enzyme reduced CML in aged human lens proteins, arterial tissue and skin. The study did not involve dosing living humans or demonstrate clinical benefit, but it’s the first POC at reversing advanced glycation endproducts from proteins.

To show the excitement of the geroscience field about this, I will directly quote Aubrey De Grey’s LinkedIn post “This is a massive breakthrough in arguably the single most neglected aspect of aging, extracellular matrix damage. Outstanding researchers have tried and failed for decades to do this. Massive kudos to Aaron and his team!”

Source: Nature Communications: “Reversal of protein chemical aging by enzymatic deglycation,” July 14, 2026

Have I missed any important updates from other longevity companies? Please let me know in the comments!

Stay tuned for H2 updates in December!

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🇺🇸USA🇺🇸

Don’t skip! Basic Science Differences Between BCI Companies

Before comparing the companies, we need to understand where does their BCI interface with the brain, how deep does it go, and what function is it trying to restore.

Neuralink, Paradromics, and Axoft are intracortical BCIs. They enter brain tissue to access higher-resolution neural activity. Paradromics’s BCI goes just below the surface. Neuralink is inserted roughly 1–4 mm into the cortex, close enough to record from individual neurons. Axoft pushes the depth thesis further to ~10mm to reach cortical and potentially shallow subcortical tissue. The purpose of this deeper access is bandwidth: better decoding of motor intent, communication, cursor control, robotic-limb control, and other forms of functional restoration in patients The trade-off is biological cost. Penetrating the cortex can improve signal quality, but it also increases surgical complexity, tissue response, inflammation risk, and the difficulty of maintaining stable recordings over years.

Precision Neuroscience and Science Corporation are surface-based BCIs. Their devices sit on top of the cortex, typically in the subdural space, without penetrating brain tissue. Precision’s Layer 7 array is a thin cortical surface interface; Science Corporation’s biohybrid sensor follows a related surface-level logic. These systems give up some single-neuron resolution but aim for lower tissue damage, easier implantation, better biocompatibility, and potentially more scalable clinical deployment. Their bet is that many early BCI applications may not need maximum bandwidth; they need enough signal with less risk.

Non-invasive BCIs such as the one ideated by Merge Labs (early R&D) are focused on building a broadly accessible brain–AI interface without conventional implanted hardware.

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Neuralink – scaling human trials and next‑generation devices

Elon Musk’s Neuralink is arguable the best publically recognized BCI.

• Trial expansion and next‑gen implants. A January 2026 update reported that Neuralink’s PRIME Study (the company’s brain‑computer implant trial) nearly doubled participation compared with September 2024; 21 patients were enrolled. Elon Musk announced a next‑generation implant with triple the channel count, expected later in the year. Patients with paralysis used the current device to play video games, browse the internet and move a computer cursor. Musk claimed the goal is eventually to restore full bodily function.

• Production ambitions. Musk told Reuters that Neuralink plans high‑volume production of its BCI device in 2026 and aims to automate the surgical procedure. Human trials began in 2024 after the FDA lifted its clinical hold; by September 2025 twelve participants had been implanted and the company had raised $650 million.

• Other advances: Neuralink has progressed on several fronts including an active robotic arm control trial (often referred to as CONVOY or similar feasibility study) allowing quadriplegic and ALS patients to use the N1 implant for precise control of assistive robotic arms to perform reaching, grasping, and everyday physical tasks. Their clinical arm is expanding in a particularly prolific manner with international trial expansion via the GB-PRIME study in the UK with multiple patients already implanted plus activity in Canada and other regions

Axoft – bio‑inspired implants and Series A financing

Axoft is the BCI company built around the softness problem. They argue that the bottleneck for chronic brain implants is mechanical mismatch: conventional electronics are far stiffer than brain tissue, which contributes to scarring, drift, and unstable signals. Its new material probes are designed to enter brain while behaving more like the tissue around them, combining high-density recording/stimulation with a softer, more biocompatible interface. That makes Axoft a “deep access, lower damage” bet: it wants the signal advantages of intracortical implantation without the long-term biological penalty that has historically made penetrating BCIs hard to scale.

• $55 million Series A (April 29 2026). Axoft, a U.S. neurotechnology startup, raised an oversubscribed $55 million Series A to expand global clinical trials and build a GMP facility.

• Novel material – Fleuron™. Axoft’s implantable BCI uses Fleuron™, a bio‑inspired material that is 10,000× softer than polyimide and provides 8× more region access and 32× more sensors per thread than conventional probes.

• Clinical progress. The company has implanted its iBCIs in more than 11 patients, recording neural activity through different cortical and subcortical layers. Axoft intends to expand clinical trials globally and commercialize the material for other biomedical applications.

Paradromics – APEX Partnership

Paradromics is the oldest out of the main BCI players. Paradromics is basically Neuralink’s less-funded, less-flashy, more speech-obsessed cousin. Not tested in humans yet for chronic results (tested for acure readout - 10 min implantation and removal).

• Clinical trial preparation and site expansion: Recruitment opened at key sites (including University of Michigan and Massachusetts General Hospital). The Connect-One study advanced with IRB approvals and site activations for long-term implants focused on safety, speech decoding, and computer control for patients with ALS, stroke, or spinal cord injury.

• Academic partnership program. On 17 March 2026, Paradromics launched the APEX Partnership Program to connect academic researchers with its Connexus brain–computer interface. The Connexus system reportedly transfers >200 bits per second—comparable to human typing—and is already in a first‑in‑human study. Collaborators include Stanford University, Massachusetts General Hospital, the University of Pittsburgh, the University of Michigan and UC Davis. In my opinion, paradromics’ decision to open its platform to academics mirrors GPU cloud providers inviting developers early. The company aims to build an ecosystem of applications before commercialization, and scouts for young talent. VC interest should track whether these partnerships convert into licensing or co‑development agreements.

✨Random notes: If you are thinking of starting a company, do your research and name it in the way that is not dangerously simmilar to other companies in the similar industry (here broader biomed). I keep confusing Paradromics with Paragonix for organ storage.✨

Precision Neuroscience – partnerships and AI leadership

Precision, founded by Neuralik co-founder Benjamin Rapoport, positions itself as an AI‑first BCI company. They have one of the largest high-resolution human neural datasets in the industry and are actively building neural foundation models and advanced machine learning pipelines on top of this data. Their core strategy is to use AI to turn raw high-resolution cortical recordings into reliable, real-time decoding (speech, movement intent, etc.). They emphasize building robust AI systems that can generalize across patients rather than relying purely on hardware advantages.

• Integration with Medtronic (January 12 2026). Precision Neuroscience announced that its Layer 7 cortical surface implant would be integrated with Medtronic’s StealthStation navigation system. The collaboration combines real‑time electrode data with surgical navigation and marks one of the first major device‑company partnerships in BCI.

• Chief AI and Data Officer hire (April 8 2026). Precision brought on Craig Mermel, formerly of Google, as Chief AI & Data Officer to oversee neural‑data pipelines and machine‑learning strategy. The company noted that its Layer 7 implant has been tested in over 75 patients and has amassed a sizable neural dataset.

• Partnership with UChicago Medicine (April 30 2026). Precision partnered with UChicago Medicine to study AI‑driven sensorimotor function and develop neuroprosthetic applications. The Layer 7 microelectrode array captures high‑resolution neural activity and has 510(k) clearance for up to 30 days of continuous recording. The company highlighted that it has raised $180 million and continues to build a clinical evidence base.

Science Corporation – financing and biohybrid BCIs

Founded by Max Hodak (co-founder of Neuralink), Science Corporation is positioning itself as the anti‑Neuralink pursuing retinal and surface implants rather than deep brain probes. For their BCI, they use optogenetics, which is an estabished neuroscientific method to modulate neuronal behavior through light and genetically modified cells. Instead of soft threads that just sense neurons’ signals, they genetically engineer living neurons to express light-sensitive proteins. These modified neurons are embedded in a surface implant and can be precisely activated or inhibited using light from integrated micro-LEDs. This allows the device to both record neural activity and stimulate the brain through biological intermediaries rather than direct electrical stimulation.

• $230 million Series C (March 5 2026). Science Corp closed a $230 million Series C round to commercialize its PRIMA retinal implant and expand into other vision disorders. In an early trial, 80 % of patients regained functional central vision.

• Executive hire (March 31 2026). Neurosurgeon Murat Günel joined as medical director for BCIs, overseeing surgical programs for a planned biohybrid implant that uses living neurons.

• Partnership with Neurosoft Bioelectronics (Feb 20 2026). Science partnered with Neurosoft to provide its full BCI ecosystem to other developers, reducing the cost of building a platform from $75–100 million to under $5 million. The collaboration aims for soft, high‑bandwidth implants that cover the full cortex.

• Preparing first human trial (April 14 2026). TechCrunch reported that Science Corporation is preparing the first human trial for its 520‑electrode biohybrid sensor, which sits on top of the cortex and may avoid penetrating tissue.

Neurosoft Bioelectronics – soft, stretchable electrodes and seed round

Neurosoft’s seed round underscores growing interest in soft materials for BCIs. The ability to record large-scale cortical activity without damaging tissue could be transformative. Early human data and partnerships (e.g., with Science Corp) will be key indicators.

• $7.5 million seed round (May 20 2026). Neurosoft Bioelectronics raised $7.5 million to advance its soft, stretchable brain interface platform. The electrodes are up to 1,000× more compliant than conventional materials, cover 30× more cortex, and enable full cortical access without penetrating tissue. The technology has been tested in 10 patients across two trials, and the company plans to build a neural data foundation model and has more than 25 patents.

Merge Labs (OpenAI‑backed) – non‑invasive molecular/ultrasound approach

As of May 2026, Merge labs is in the realy research stage, without any hints of a proof of concept. It is pursuing a broader BCI based on non-invasive ultrasound, molecular tools (not specified), and AI decoding. The idea is to avoid the central trade-off of implanted BCIs, where better signal usually requires putting hardware into or onto the brain. Time will tell. Sam Altman has a record of backing companies at the frontier of innovation, such as Retro Biosciences in aging research, which has one drug in phase 1 clinical trials.

• Seed funding led by OpenAI (Jan 15 2026). OpenAI and partners invested $250 million in Sam Altman’s Merge Labs, valuing the company at $850 million.

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🇨🇳CHINA🇨🇳

China’s BCI acceleration in 2026 did not emerge spontaneously from startups alone. It followed a formal national industrial strategy released in August 2025: the Implementation Plan for Promoting Innovation and Development of the Brain-Computer Interface Industry (关于推动脑机接口产业创新发展的实施意见) naming BCI development as strategic industrial infrastructure. The plan explicitly called for major technological breakthroughs by 2027, establishment of national technical standards, construction of a domestic BCI industrial chain by 2030, and the emergence of 2–3 globally leading Chinese BCI companies.

The document outlined a 17-point implementation framework spanning implantable chips, flexible electrodes, neural signal acquisition hardware, decoding algorithms, neurosurgical systems, manufacturing capacity, clinical translation, rehabilitation applications, and commercialization pathways. Importantly, it also emphasized integration between hospitals, universities, manufacturers, and regulators — a structure that allows China to compress the distance between laboratory prototypes and scaled clinical deployment. Provincial governments eg. Jiangxi subsequently began establishing dedicated neurotechnology industrial zones and funding programs linked directly to the national roadmap.

This strategy became even more consequential in March 2026, when BCIs were incorporated into China’s 15th Five-Year Plan (2026–2030) as an official “future industry” alongside embodied AI, quantum technology, 6G communications, and fusion energy. In Chinese industrial policy language, that designation matters enormously. It signals long-term state prioritization across financing, infrastructure, regulation, talent recruitment, procurement, and manufacturing support. By the first half of 2026, companies such as NeuroXess, Neuracle and StairMed had become components of a coordinated national effort to industrialize BCIs at scale. So what’s the most recent news?

NeuroXess

NeuroXess (脑虎科技), founded in Shanghai in 2021, is one of China’s leading invasive brain–computer interface companies and has emerged as a flagship player in the country’s national BCI strategy. Unlike Neuralink’s deeply penetrating intracortical threads, NeuroXess primarily focuses on ultra-flexible polyimide-based cortical electrodes designed to reduce tissue damage, inflammation, and long-term mechanical mismatch with the brain while maintaining high-resolution neural recording capabilities. The company develops a vertically integrated “full-stack” platform spanning implantable electrodes, wireless neural signal acquisition hardware, decoding algorithms, and implantation systems. NeuroXess has publicly demonstrated a 256-channel fully implantable wireless BCI system capable of cursor control, robotic interaction, and Mandarin speech decoding, reporting motor decoding speeds of 5.2 bits per second and approximately 71.5% accuracy for direct Mandarin neural decoding

• Super Factory (January 2026) NeuroXess reportedly launched a large-scale BCI manufacturing project (“super factory”) in Nanchang, Jiangxi Province, aimed at scaling implantable BCI production beyond research quantities.

• Clinical Report (February 22, 2026) TechCrunch reported that NeuroXess had completed more than 50 flexible implantable BCI clinical procedures by mid-2025, making it one of the most clinically active invasive BCI groups discussed publicly in China.

StairMed

StairMed (阶梯医疗), founded in Shanghai in 2021 (see the pattern?) has positioned itself as a direct competitor to Neuralink in minimally invasive implantable brain–machine interfaces. The company develops a vertically integrated platform spanning ultra-flexible neural electrodes, wireless implant systems, decoding algorithms, and proprietary surgical robotics. StairMed’s core technological differentiator is its extremely thin flexible electrode architecture (reportedly as small as one-hundredth the width of a human hair and significantly softer than Neuralink’s.

• $72.8 million financing (April 2 2026). Shanghai‑based StairMed closed a strategic round worth RMB 500 million (~$72.8 million) led by Alibaba, with participation from Tencent, OrbiMed, Fountainbridge Capital and others. The round marks a rare joint investment by Alibaba and Tencent, underscoring strategic importance.

• Technology and clinical roadmap (March 2026). The company has received access to China’s NMPA Green Channel for innovative medical devices. There is information their proprietary surgical robot is operational and they plan to implant their 256‑channel wireless invasive BCI (WRS02) (Neuralink has 1,024 channels) in 40 people by the end of this year. Chinese media called it the first BCI clinical trial in china, but i didn’t manage to find any registered trial information, so let’s stay cautious. Nevertheless, they are cleared for an accelerated approval path

• There are news that they are expanding their indication into closed-loop neuromodulation systems for Parkinson’s disease and epilepsy.

Neuracle – first commercial BCI approval in China

This company made headlines all over the world for becoming world’s first commerically available invasive BCI. Neuracle’s approval demonstrates regulatory momentum in China. This could catalyze adoption and attract capital to domestic players.

• Regulatory approval (March 13 2026). According to reports compiled by MassDevice, China’s National Medical Products Administration (NMPA) granted Neuracle the country’s first approval for a commercial implantable BCI. The coin‑sized wireless device sits on the brain’s surface and is designed to restore hand function in patients with spinal cord injuries.

• Market implications. The approval marks the first time an invasive BCI can be sold in China for clinical use. It highlights China’s ambition to compete with Western BCI firms and may create a domestic pathway distinct from U.S. FDA requirements.

Gestala – ultrasound‑based non‑invasive BCI

Gestala (格式塔科技), founded in Chengdu in January 2026, is China’s first company dedicated specifically to ultrasound-based brain–computer interfaces. The company was cofounded by Phoenix Peng, former executive at NeuroXess, together with billionaire entrepreneur Tianqiao Chen, founder of Shanda Interactive and the $1 billion Tianqiao and Chrissy Chen Institute neuroscience initiative. To my understanding, their tech idea is the same in principle as Merge Labs, discussed earlier. The company initially targets chronic pain, stroke rehabilitation, PTSD, depression, and other neurological disorders using benchtop ultrasound systems before transitioning toward wearable consumer-grade neurotechnology. They aim to complete their MVP by the end of the year.

• $21.6 million seed round (March 11 2026). Two months after launch, Gestala raised $21.6 million at a valuation between $100–200 million. The round was co‑led by Guosheng Capital and Dalton Venture; commitments totaled more than $58 million.

• Impressive Advisory Board: During the first half of 2026, the company rapidly assembled an unusually high-profile scientific advisory network, including former Neuralink clinical partnerships lead Bashar Badran, Cambridge neuroscientist Trevor Robbins, and Fudan University brain scientist Jianfeng Feng.

• Robotics partnership (January 2026). Gestala signed a strategic partnership with Chinese robotics company Fourier, positioning ultrasound BCIs alongside embodied AI and rehabilitation robotics.

Cross Pacific Market and Investment Trends

• Capital inflows. The first half of 2026 saw several nine‑figure rounds (Science Corp $230 M Series C, Axoft $55 M Series A, OpenAI‑backed Merge Labs $250 M seed, Paradromics partnership program) alongside significant Chinese funding (StairMed $72.8 M, Gestala $21.6 M). Soft materials and ultrasound BCIs attracted seed funding, suggesting diversification away from rigid implants.

• Material innovation. Across companies, a common theme is biocompatibility. Axoft’s Fleuron material is 10,000× softer than polyimide; Neurosoft’s electrodes are 1,000× more compliant; Science Corp’s biohybrid sensor uses living neurons; Chinese firms tout ultra‑flexible microelectrodes. These advances aim to reduce inflammation, improve signal longevity and enable high‑density recording.

• Regulatory progress. While no new FDA approvals occurred, Precision Neuroscience’s 510(k) clearance for 30‑day recordings and Neuralink’s ongoing trial expansion show increasing engagement with regulators. Neuracle’s NMPA approval may spur a regulatory race.

• AI‑driven data strategies. Companies like Precision Neuroscience and Merge Labs emphasize foundation models and AI pipelines; Gestala is building an “Ultrasound Brain Bank”. VC investors should evaluate data rights, privacy frameworks and the quality of neural datasets.

• Competition categories: The benchmark and comparison becomes not just “brain chip vs brain chip” but “implant + surgery + decoder + indication”

Conclusion

The first half of 2026 marked a transition for BCIs from experimental prototypes to commercial‑grade platforms. Capital flowed to both invasive and non‑invasive approaches, with significant participation from big tech (OpenAI), med‑tech giants (Medtronic) and Chinese conglomerates (Alibaba, Tencent). Regulatory milestones in China and expansions of clinical trials in the U.S. set the stage for competitive dynamics that span continents. Material innovations promise better biocompatibility, while AI strategies aim to convert neural data into scalable products. For investors and analysts, due diligence should focus on the clinical evidence, regulatory pathways, manufacturing capabilities and data strategies of each company. The next inflection point will likely be the outcomes of ongoing human trials and the first demonstrations of safe, high‑bandwidth, minimally invasive BCIs.

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For most of modern biotech, biology itself was never the rate limiter. Throughput was. Although sequencing costs collapsed faster than almost any technology curve in industrial history (Check out a great deal in Human Longevity Inc in memoriam of Craig Venter, who made cheap sequencing possible) , wet-lab iteration remained stubbornly physical: graduate students pipetting liquids by hand, fragmented inventory systems, irreproducible protocols buried in supplementary PDFs, CRO coordination through email chains, freezers full of chaotically labeled samples, and experimental timelines measured in weeks because a single assay queue backed up an entire program.

Software scaled because computation became standardized. A developer could run the same application on different servers without changing the code. That is what made Amazon Web Services powerful: compute became interchangeable infrastructure.

Biology does not behave that way. Experimental systems are still tightly coupled to specific hardware, workflows, and lab conditions. A protocol built for robotic liquid handlers from Hamilton Company often requires recalibration on systems from Tecan because the robots move differently, dispense liquids differently, and run different software. Similarly, automated workflows developed inside Synthace may not transfer cleanly into cloud laboratory environments like Emerald Cloud Lab because the orchestration systems and instruments are different.

Even small variables like reagent batches, humidity, incubation timing, or how aggressively liquids are pipetted can change biological results. Biology still lacks the clean abstraction layers that made cloud computing possible. So when people want to push their comapny PR as “AWS of biology,” the real opportunity is not infinitely portable experiments. It is building the infrastructure that makes biology more standardized, reproducible, and programmable than it is today.

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The last decade produced an enormous increase in computational capability: foundation models, generative protein design, multimodal biological embeddings. But wet-lab throughput remains structurally constrained. The bottleneck is no longer hypothesis generation. It is experimental execution density. Most AI-native biotech companies eventually collide with the same problem: they can generate candidate space faster than they can validate it. A competent computational biologist can spin up a GPU cluster, run inference on a 70B parameter model, and tear down the infrastructure in an afternoon. A wet-lab scientist trying to run a comparable experiment will spend weeks on protocol optimization, reagent sourcing, instrument calibration, and data cleaning before generating a single interpretable result. That delta is the actual market opportunity. The question is who captures it and how.

The LIMS Problem Is Not What You Think

Laboratory information management systems (LIMS) have existed since the 1980s. The fact that they remain a genuine pain point in 2026 tells you something about the structural difficulty of the problem. Benchling, a software platform for managing biological R&D workflows and experimental data, is the canonical success story, and it’s worth understanding precisely why. Benchling won by starting with molecular biology workflows like sequence editing, construct design, cloning, where the data model was tractable, generating habitual daily engagement from bench scientists, and then expanding upward into electronic lab notebooks and data management once it owned the scientist’s working memory. It then went further: sample lineage, compliance, permissions, inventory, experimental coordination across regulated environments. The company embedded itself into operational workflows deep enough that displacement became organizationally expensive even when competing products were technically superior. That’s closer to ERP (entreprise resource planning) than laboratory software.

Importantly, Benchling’s strategic position improves as biology becomes more computationally orchestrated. AI-generated experimental design increases the importance of standardized execution environments because model outputs only compound in value if downstream experimental systems remain structured enough to absorb and reproduce them. Most investors focus on the model layer. The execution layer into which models pipe their outputs may end up structurally stronger, for the same reason that database infrastructure often outlasts the applications built on top of it.

The companies that failed (and there were many with genuinely good technology) largely underestimated this dynamic. They built comprehensive systems first and tried to migrate scientists away from existing tools. Scientists are conservative about workflow changes for defensible reasons: a protocol that works is worth protecting, and a software migration that breaks an assay mid-campaign has real cost. LabVantage, IDBS, and Dotmatics all have meaningful enterprise presence, but their growth profiles look nothing like Benchling’s, partly because they approached the market as IT infrastructure rather than scientist tooling. Dotmatics’ acquisition by Insightful Science and subsequent consolidation plays represent the other strategic path: horizontal aggregation of a fragmented market rather than organic platform expansion (which is not without issues; see paragraphs below for horizonal vs vertical integration in biotech). Whether that creates durable value or just a bigger but still-fragmented bundle remains an open question.

The data locked inside a pharma company’s LIMS (decades of assay results, failed compound libraries, dose-response curves) is strategically valuable in ways nobody has fully monetized yet. The vendor that owns the schema owns the key.

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Hardware Is Not Commoditizing the Way People Expect

There’s a persistent assumption that lab automation hardware will commoditize like server hardware did; that liquid handlers become fungible, the software layer captures the margin, and liquid handling companies become interchangeable suppliers. This is probably wrong, and the reason is interesting. The biomechanics of liquid handling are genuinely complex. Aspirating 200 nanoliters of a viscous protein solution without introducing bubbles, carryover, or evaporation artifacts requires precision engineering refined over decades. Hamilton’s VENUS software is genuinely unplesant with an interface that looks like ealy 2000 and documentation that rewards persistence rather than clarity. But nobody switches away from Hamilton systems because the physical reliability of the instrument is hard to replicate, and every protocol in the lab is written against Hamilton behavior specifically. The switching cost is embedded in the protocol library, not the instrument contract.

The more interesting development is what happens when automation infrastructure becomes tightly coupled to machine-learning-driven iteration. Once closed-loop optimization enters biology throughput infrastructure starts behaving like computational infrastructure. Historically, Hamilton and Tecan and Beckman Coulter were viewed primarily as instrument vendors. Increasingly, they look more like control points within biological compute systems. That’s a different strategic position, and one that their current pricing and go-to-market strategies don’t yet fully reflect.

Opentrons identified a different segment: academic labs, startups, and applications where $150K for a Hamilton is prohibitive. The OT-2 is not a Hamilton competitor but a different class of instrument, lower throughput, less precision, more variability (like iPhone 17 vs iPhone 13). But it’s open, Python-programmable, and costs $10K. The Flex platform moved upmarket. What’s strategically interesting about Opentrons is less the hardware and more the cultural implication: it potentially onboards a generation of scientists who learn to think about automation natively, in code, from their first lab job. That’s a slow-compounding shift in what scientists expect from experimental environments, which has downstream effects on the market for everything above the hardware layer.

Formulatrix is worth examining because it represents deep vertical specialization carried to near-monopoly: crystallography and imaging workflows, where ROCK Imager systems have become the standard for protein crystallography imaging to a degree that is almost uncomfortable from a competitive standpoint. Formulatrix doesn’t care whether your drug discovery hypothesis is correct. It needs you to be running crystallography screens. And switching imaging platforms mid-project requires revalidating months of data. That’s a defensible position that doesn’t depend on being the best instrument in the abstract, it depends on being embedded in a workflow where switching is costly.

Cloud Labs: The Contract Fab Analogy Is Better Than AWS

The cloud lab concept, remote access to robotic experimentation platforms via software-defined protocols, is clearly correct in theory. The ability to submit an experimental design and receive structured data back, without managing instrument uptime, reagent inventories, or technician schedules, is obviously valuable (Check how cool and efficient it is in practice by seeing the autonomus lifestar2 footage from Insilico Medicine and then their pipeline)

Emerald Cloud Lab has been building toward this since 2012: a proprietary specification language (SciLang), a full instrument fleet, experiments defined entirely in software. Strateos went a similar direction. Arctoris built a UK-based cloud lab focused on pharmacology assays for drug discovery specifically. The model is right. The adoption curve has been slower than expected.

The AWS analogy breaks down quickly here because biological experiments are not cleanly virtualizable. Tacit operational knowledge still matters enormously. Small procedural deviations frequently alter outputs. Biological systems remain highly context-sensitive in ways that compute workloads are not. But the failed analogy obscures the more important point: centralized experimental infrastructure may become economically dominant even without full abstraction. The better comparison is contract semiconductor fabrication during early industry consolidation. Most companies eventually stopped building full-stack fabrication internally not because they achieved a clean abstraction layer, but because centralized operators achieved superior throughput economics, process consistency, and tooling specialization that internal teams couldn’t match on any reasonable capital budget (read Chris Miller’s “Chip War” for a clear understanding of the current semiconductor situation).

Biology appears to be moving in the same direction, although more slowly due to biological variability and regulatory friction. The path to enterprise adoption for cloud labs requires either regulatory acceptance of remote execution for IND-enabling studies (slow) or a sufficient track record that internal risk committees get comfortable, which is also slow. So cloud labs have found their natural early market in academic collaborations, early-stage drug discovery, and applications where iteration speed matters more than GLP compliance. Argonaut Bio took the narrower approach: synthetic biology workflows specifically, where the customer is more likely to be a startup or internal platform team with fewer regulatory constraints on individual experiments. The narrower focus may be correct. There’s a version of the cloud lab market that looks like one dominant platform, and a version that looks like vertical SaaS — specialized platforms owning specific workflow categories. Given the difficulty of building general-purpose biology infrastructure, the vertical version seems more likely in the near term.

Synthetic Biology Tooling: Where Scientific and Commercial Timelines Diverge Most

The design-build-test-learn cycle in synthetic biology has gotten dramatically faster over the last decade. DNA synthesis costs have dropped roughly 10,000-fold since the early 2000s, sequencing costs have dropped more, and protein structure prediction is tractable in ways that felt implausible five years ago. But the infrastructure to actually run high-throughput genetic engineering campaigns is still fragmented and largely manual at most organizations.

Twist Bioscience solved the synthesis bottleneck using silicon-based DNA synthesis, achieving cost structures that make large library generation economically sensible. The strategic insight was that DNA synthesis, done on silicon at scale, could look more like semiconductor manufacturing than chemical synthesis. Twist has real competitive advantages in yield and error rate at long constructs. IDT (now part of Danaher) dominates shorter oligos with the advantage of Danaher’s operational discipline and customer relationships. The synthesis market has effectively bifurcated: commodity short oligos where IDT and a handful of others compete on price, and longer synthetic genes and complex libraries where Twist holds a meaningful position. But synthesis is only one step.

The harder problem is the rest of the DBTL stack. Who stores and tracks the constructs? Who manages transformation and selection? Who runs the assay? Who cleans and structures the data? Ginkgo Bioworks built this stack internally and has been attempting to sell access to it as a platform service: the Codebase licensing model, where customers access Ginkgo’s organisms and protocols without rebuilding the infrastructure themselves. The commercial reality has been harder than the vision suggested, and the diagnosis is worth being precise about. Ginkgo’s actual moat is the organism and pathway library plus accumulated experimental data, not the automation infrastructure per se, though they’re linked. The market initially priced the company as if organism engineering would scale with software-like marginal economics. That assumption turned out to be overly optimistic because biological systems retained too much context dependence, customer-specific variability remained high, automation gains were uneven, and biological standardization progressed more slowly than modeled.

Dismissing the underlying infrastructure thesis entirely is probably also incorrect. Large-scale organism engineering pipelines, automated assay systems, protocol libraries, strain optimization workflows, and biological process data accumulate strategic value over long time horizons. Infrastructure businesses frequently look operationally messy during early market formation because standardization hasn’t stabilized yet. The same pattern appeared repeatedly in cloud computing, semiconductor tooling, and industrial automation. Ginkgo’s current challenges are partly execution and partly market timing, not necessarily evidence that the platform model is wrong.

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Data Advantages: Loops Beat Snapshots

Every pitch deck in bio-infrastructure mentions data network effects. A true data network effect requires that more users generate data that makes the platform more valuable for all users. In biology, this is harder to achieve than people admit. Experimental data from one customer’s cell line in one growth condition is not obviously useful for another customer’s cell line in a different condition. The context-dependence of biological data means raw volume is much less valuable than curated, structured, annotated datasets from controlled experiments.

The more defensible framing is not static data assets but continuously compounding experimental feedback loops. Data generated through standardized execution systems becomes disproportionately valuable because it remains computationally interoperable over time: you can train on it, compare across it, and use it to calibrate future experiments. Data collected on heterogeneous, poorly documented protocols is largely stranded. This is a meaningful distinction that changes which companies actually have durable data positions versus which ones have accumulated volume that they can’t use (which is aslo one of the reasons why there is no foundation model for cryo yet).

The relevant distinction is not how much biological data a company has collected. It is whether that data was generated under standardized enough conditions to remain computationally useful as models improve.

The Regulatory Asymmetry Nobody Talks About Enough

One structural advantage that bio-infrastructure companies have over their customers is regulatory positioning. A LIMS vendor or lab automation company selling to pharma doesn’t need FDA approval to operate. Their customers do. This creates an asymmetry where the infrastructure layer can move faster, experiment more freely, and generate revenue from multiple customers simultaneously, while each customer faces the full weight of biotech/medtech regulatory timelines. The infrastructure company doesn’t inherit the risk of any single drug program failing. It gets paid regardless of whether the science works (unless it’s their fault, obv).

This changes when infrastructure is used for GMP manufacturing or regulated assays. LabVantage and IDBS have substantial businesses in validated LIMS systems embedded in QC workflows for GMP facilities. This is a structurally different market from early R&D tooling. Validation is expensive, change control is slow, and switching costs are enormous. The average validated LIMS replacement at a major pharmaceutical company is a multi-year project costing tens of millions of dollars. Once you’re in, you’re in for a decade. That’s an extremely durable revenue stream but also slow growth and limited ability to update the product, because every update requires revalidation. The startups trying to enter this segment have to offer something sufficiently compelling that customers will absorb the validation cost; the incumbents benefit from a status quo that is physically difficult to disrupt.

The Missing Layer: Biological APIs

Software engineering has a well-developed concept of APIs": standardized interfaces that let you call a function without caring about the implementation underneath. Biology doesn’t have this, and the absence is more fundamental than it might seem. When a software team integrates with Stripe’s payment API, they get deterministic behavior: the same input produces the same output, errors are typed and documented, the interface is stable across versions. When a biology team tries to call a “run CRISPR screen” function despite using the same protocol, same reagents, same cell line, they get variable outputs, undocumented failure modes, and results sensitive to ambient humidity, reagent lot numbers, and which technician ran the experiment on which day.

The effort to build something API-like out of biology is a deep bet in the bioengineering infrastructure space. Synthace’s platform is one articulation: a high-level protocol language that abstracts over specific instruments and generates executable steps for available hardware, plus structured data capture that makes results comparable across runs. The technical challenge is that the abstraction layer has to be biologically meaningful. It’s not enough to say “mix these two things”; you have to specify temperature, timing, mixing dynamics, and dozens of other parameters that affect the result. That’s a lot of domain knowledge to encode, and the edge cases are endless. The economic challenge is that scientists are skeptical of black boxes, and the value of structured protocol specification is only visible over time, when you’re comparing run 47 to run 3 and trying to understand why the outputs diverged.

The companies that will partially solve this are likely the ones finding specific workflow categories narrow enough to make reliability achievable. Beckman Coulter’s automated cell culture systems approach biological APIs for cell expansion: specify starting conditions and target passage, system manages it. Not perfectly deterministic, but reliable enough to build on top of. As these partial APIs proliferate across workflow categories like liquid handling, cell culture, sequencing library prep or protein purification, the stack starts to look more like software infrastructure and less like artisanal science. Once experimentation itself becomes computationally orchestrated, the strategic center of gravity shifts toward whoever controls the interfaces between models, experiments, instrumentation, and validated operational systems. That is where infrastructure becomes extremely difficult to displace.

Who Captures Durable Leverage

A large portion of current biotech investing still evaluates companies primarily through scientific novelty: differentiated targets, novel modalities, proprietary models, unique datasets. Those matter, but they don’t necessarily determine who captures durable leverage. Infrastructure companies frequently become more strategically important than discovery companies because they sit directly inside iteration loops rather than depending on them.

The history of technology infrastructure suggests that the companies building durable positions are usually not the most scientifically impressive or the most technically ambitious. They’re the ones owning a chokepoint in the workflow, accumulating switching costs faster than competitors can erode them, and building data or network assets that compound over time. In bioengineering infrastructure, a few patterns stand out.

1. The companies that own the biological data model historically beat the companies that only owned the hardware. Sequencers and lab instruments eventually commoditize; structured datasets, annotations, and interpretation pipelines do not. Before AI, a lab could buy a genome sequencer and still spend months extracting meaningful insight without specialized bioinformatics infrastructure. Foundation models are beginning to compress that advantage by making biological interpretation cheaper and more portable, shifting value away from proprietary analysis layers and toward ownership of large, high-quality longitudinal datasets.

2. Vertical depth beats horizontal ambiguity. The companies with the clearest positions like Formulatrix in crystallography imaging or Twist in gene synthesis are deeply specialized. Platforms trying to be everything to everyone in biology are struggling, because “everything in biology” is too heterogeneous to serve with a single product architecture.

The important shift is not that biology is becoming software. It is that computation is colliding with a physical system that refuses to fully abstract. AI can generate hypotheses, designs, and experimental plans at extraordinary scale, but biological execution still depends on fragile workflows, tacit knowledge, instrument-specific behavior, and operational discipline. That makes infrastructure more strategically important, not less. The durable companies are unlikely to be the ones with the flashiest models or the cheapest hardware. They are the ones embedding themselves inside the experimental loop deeply enough that removing them would slow down the production of biological insight itself.

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Today’s reality in the operating room

As of 2026, static cold storage (SCS) remains the predominant standard method of donor organ preservation worldwide. This involves flushing the donor organ with a specialized cold preservation solution (typically at 4°C, such as University of Wisconsin solution or histidine-tryptophan-ketoglutarate) to remove blood and reduce metabolic activity, then storing it in a sterile triple bag or container packed with ice in a cooler for transport. This simple, cost-effective, and portable technique slows cellular metabolism and minimizes ischemic damage, allowing preservation times of 4-6 hours for hearts, 6-8 hours for lungs, 12-24 hours for kidneys, and up to 12-15 hours for livers, depending on the organ. While effective for standard donors, SCS has limitations, such as increased risk of graft dysfunction with extended times or marginal organs, leading to higher discard rates. So what are the companies whose products address that?

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1. TransMedics

TransMedics is a frontrunner in normothermic machine perfusion (NMP), with their Organ Care System (OCS) platform approved for heart, lung, and liver transplants in the U.S. The OCS is a portable “box” that keeps organs functioning ex vivo by circulating warm, nutrient-rich, oxygenated blood or a blood-based solution through them, essentially replicating the body’s conditions. This contrasts with hypothermic methods by keeping the organ metabolically active rather than slowing metabolism, which enables therapeutic interventions (e.g., adjusting electrolytes or administering medications) and functional evaluation during preservation. As of 2026, the OCS is FDA-approved for both donation after brain death (DBD) and donation after circulatory death (DCD) indications across heart, lung, and liver transplants in the U.S., and it’s CE-marked in Europe. Clinical benefits include lower rates of early allograft dysfunction (EAD, e.g., an 13% reduction compared to cold storage for livers), improved graft survival, and expanded use of marginal donor organs. Moreover, the comapny has their own aircraft fleet to further ease the supply chain for transplantation. I was also very happy to see that they have an extensive body of peer reviewed publications on the effect of their system on organs, as well as economic impact on the “industry”, for the lack of better word.

• How it works: The OCS is a fully portable, multi-organ system that uses normothermic (body-temperature, approximately 34-37°C) perfusion to mimic the human body’s environment, perfusing organs with warm, oxygenated, nutrient-enriched donor-compatible blood (often collected from the donor or supplemented). This contrasts with hypothermic methods by keeping the organ metabolically active rather than slowing metabolism, which enables therapeutic interventions (e.g., adjusting electrolytes or administering medications) and functional evaluation during preservation. As of 2026, the OCS is FDA-approved for both donation after brain death (DBD) and donation after circulatory death (DCD) indications across heart, lung, and liver transplants in the U.S., and it’s CE-marked in Europe. Clinical benefits include lower rates of early allograft dysfunction (EAD, e.g., an 18% reduction compared to cold storage for livers), improved graft survival, and expanded use of marginal donor organs.

  • OCS Heart: The system perfuses the donor heart with warm, oxygenated blood via the aorta, allowing it to continue beating rhythmically as it would in vivo. This is achieved through a sterile perfusion module that houses the organ, circulates blood, and maintains homeostasis (e.g., pH, oxygenation). Real-time monitoring includes ECG waveforms, aortic pressure, coronary flow, and lactate levels to assess viability and detect issues like arrhythmias or ischemia. Preservation times surpass the 4-6 hours typical of cold storage, enabling cross-country or international transport.

  • OSC Lung: The device combines perfusion with mechanical ventilation: lungs are inflated/deflated cyclically while perfused with warm blood through the pulmonary artery. This allows the lungs to “breathe” and exchange gases, improving condition by recruiting alveoli and clearing secretions if needed. Diagnostics focus on gas exchange metrics (e.g., PaO2/FiO2 ratio), bronchoscopy access for evaluation, and parameters like pulmonary vascular resistance. It supports extended preservation and is approved for both standard and expanded-criteria lungs, reducing primary graft dysfunction risks.

  • OSC Liver: The liver is perfused via the hepatic artery and portal vein with warm blood, sustaining metabolic functions such as bile production, glucose regulation, and lactate clearance. The system includes automated controls for flow rates, pressure, and temperature, with a bile collection reservoir for quantitative assessment. Monitoring tracks hemodynamic parameters (e.g., portal vein flow), biomarkers (e.g., ALT/AST enzymes), and bile output to evaluate graft quality and predict post-transplant performance. Viable times are extended, minimizing reperfusion injury and supporting DCD/DBD livers that might otherwise be discarded.

Financials and Market Status: As a publicly traded company (NASDAQ: TMDX), TransMedics boasts a market capitalization of approximately $4.4 billion as of early March 2026, with its stock price around $135, reflecting a 104% increase over the past year despite volatility. For 2025, the company reported full-year revenue of $605.5 million (up 37% YoY) and net income of $190.3 million, turning profitable at scale. Fourth-quarter 2025 revenue reached $160.8 million (32% YoY growth), with optimistic 2026 guidance emphasizing strategic initiatives for continued expansion. Trading at 56 times forward earnings, it’s viewed as “expensive” but promising, with analyst fair value estimates ranging from $144 to $240 per share, underscoring its leadership in reinventing transplant logistics amid high demand.

2. XVIVO Perfusion

XVIVO, a Swedish company, specializes in ex-vivo organ perfusion across multiple organs, with a portfolio including hypothermic, normothermic, and sub-normothermic options. Their PERFADEX Plus static cold-storage lung preservation solution is used in over 90% of lung transplant clinics worldwide, emphasizing oxygenated perfusion to maintain cellular health.

How it works:

• Kidney Assist Transport: A portable hypothermic pulsatile perfusion device that pumps cold, oxygenated solution through the kidney’s vessels for up to 24 hours, reducing ischemia damage.

• Liver Assist: Flexible protocols for hypothermic oxygenated perfusion (HOPE/DHOPE) or normothermic perfusion, circulating fluids to support metabolism and assess viability.

• XPS (Ex-Vivo Lung Perfusion): An integrated platform that perfuses and ventilates lungs with oxygenated solution, allowing functional testing like gas exchange.

Key features: Customizable temperatures, real-time monitoring, and compatibility with their PERFADEX Plus solution for lung preservation. This tech extends preservation, enables organ evaluation, and boosts utilization rates.

Financials and Market Status: Publicly listed on Nasdaq Stockholm (XVIVO.ST), XVIVO Perfusion has a market capitalization of around $600 million as of March 2026, with its stock trading at approximately $19.82. Trailing twelve-month revenue stands at 812 million SEK (about $77 million USD), with gross profit of 599 million SEK and EBITDA of 138 million SEK, though quarterly revenue growth dipped slightly by 0.6% YoY recently. The company targets EBIT over 20% and EBITDA over 30% by 2027, focusing on profitable growth in its dominant lung transplant segment amid a stable Nordic market position

3. OrganOx

OrganOx focuses on liver preservation with their metra system, a fully automated NMP device that’s FDA-approved and used globally. It’s designed to keep livers viable for extended periods under near-physiological conditions.

How it works: The metra perfuses the liver with oxygenated blood at body temperature, maintaining functions like bile production and glucose metabolism. It automates fluid circulation, temperature control, and monitoring, preserving organs for up to 24 hours (12 in some regions).

Key features: Viability testing during perfusion, procedural optimization, and a user-friendly interface. This allows clinicians to assess organ quality in real-time, reducing uncertainty.

Financials and Market Status: Acquired by japanese Terumo Corporation in August 2025 for a reported $1.5 billion valuation, OrganOx is now integrated into a larger medtech ecosystem, marking one of the UK’s largest medtech exits. Prior to acquisition, it raised $45.4 million across nine funding rounds, with the latest Series D in February 2025. Post-acquisition, Terumo projects OrganOx to contribute about 9 billion JPY (roughly $60 million USD) in revenue for the five-month period from November 2025 to March 2026. As a subsidiary, it benefits from Terumo’s resources, strengthening its market position in liver perfusion amid growing demand for normothermic technologies

4. Paragonix Technologies

Paragonix offers advanced hypothermic oxygenated preservation and transport systems for heart, liver, lung, and kidney, bridging the gap between static cold storage and full perfusion. Acquired by Getinge in 2024, their devices emphasize controlled cooling with monitoring.

How it works: Systems like SherpaPak (heart), LIVERguard (liver), and BAROguard use hypothermic oxygenated technology to maintain a stable cold environment (without freezing) while circulating minimal fluids for oxygenation. Real-time tracking via the Paragonix App monitors temperature, location, and pressure.

Key features: 24/7 clinical support, integration with GUARDIAN registries for data-driven insights, and extended transport times over traditional ice boxes.

Financials and Market Status: Acquired by Getinge in September 2024 for $477 million, Paragonix was previously private and had raised $39.3 million in funding, including a $24 million Series B in 2023. Specific revenue figures are not publicly disclosed post-acquisition, but as part of Getinge (market cap ~$5 billion), it contributes to the parent’s cardiovascular and life sciences segments. Market-wise, the acquisition enhances Paragonix’s global reach, positioning it as a key player in hypothermic transport amid investor interest in organ preservation innovations.

5. Bridge to Life

Bridge to Life provides hypothermic oxygenated perfusion solutions, with the VitaSmart system as their flagship for liver preservation. They’re known for simplicity and FDA-cleared innovations in HOPE technology. It’s the first FDA-cleared HOPE device in the U.S.

How it works: VitaSmart pumps cold, oxygenated solution through the organ’s vessels, maintaining viability during transport and storage. It’s automated for ease, focusing on nutritional perfusion to prevent reperfusion injury.

Key features: Portable design, compatibility with their Belzer UW solutions, and global support for procurement.

Finantials: As a private company, Bridge to Life does not disclose detailed financials publicly. It has a history of strategic growth through acquisitions, including Organ Recovery Systems in 2019, and is backed by experienced leadership with a track record in medtech financings exceeding $1 billion aggregate. Market-wise, it holds a strong position in organ preservation solutions, focusing on improving transplant success in a growing sector, though specific revenue or valuation data remains proprietary.

6. Organ Recovery Systems

A pioneer in hypothermic machine perfusion, Organ Recovery Systems’ LifePort series is trusted for kidney and liver, with over 275,000 kidneys preserved since 2003.

How it works: LifePort Kidney/Liver Transporters pump a cold physiologic solution through the organ in a sterile, sealed environment, with pulsatile flow for kidneys and precision control for livers (hepatic artery/portal vein). It combines dynamic perfusion with backup static storage.

Key features: Portable for air/ground travel, encrypted data transmission, intuitive app with multilingual training, and visual flow confirmation.

Impact: Boosts 1-3 year graft survival, enables daytime scheduling, and supports high-volume centers (e.g., 400-500 perfusions/year). Backed by 60+ studies and 10-year data.

Financials and Market Status: Operating as a subsidiary of Bridge to Life since its 2019 acquisition, Organ Recovery Systems is private with no public financial disclosures. Prior to the merger, it raised $26.9 million in funding and was profitable. Its market status benefits from integration with Bridge to Life, maintaining a solid foothold in kidney and liver perfusion within the broader organ recovery ecosystem, contributing to industry growth projected at 12-14% CAGR.

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How does this relate to organ banking by vitrification?

Machine perfusion is already teaching the field how to cannulate organs reproducibly, control vascular resistance and flow, monitor injury in real time, and build the transport-grade infrastructure needed to keep a graft under continuous supervision outside the body. Those capabilities matter directly for vitrification, because it requires uniform CPA loading and washout through the native vasculature, minimization of edema and endothelial injury, tight control of thermal gradients, and reliable functional readouts before and after rewarming. A major bottleneck is that the concentrated cryoprotectant solutions needed for vitrification (as of 2026) become highly viscous at the low temperatures preferred for toxicity reduction, making perfusion progressively more difficult exactly where gentler loading would otherwise be desirable. Higher viscosity increases vascular resistance, worsens flow heterogeneity, limits penetration into the microvasculature, and raises the risk of underperfused regions that later form ice or suffer solute injury. In that sense, today’s perfusion platforms could be creating the operational backbone for CPA loading and unloading perfusion circuits, disposables, sensors, logistics networks, trained recovery teams, and outcome-based validation frameworks.

What do you think? Did I miss any companies? Have you heard of any of these companies before?

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To move the needle on organ banking, and eventual whole organism POC, we must prioritize functional validation: the proof that a biological system doesn’t just look “fine,” but can still perform its job. Cryopreservation has reached the point where structural validation is no longer an adequate metric of progress; functional performance must be the new gold standard.

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Structural vs. Functional

Structural validation tells us the “parts” are there. Functional validation tells us the “machine” still runs. In neurobiology, for instance, a vitrified and rewarmed slice of the hippocampus might show intact synaptic densities under a microscope. However, without electrophysiological testing such as Long-Term Potentiation (LTP) protocols, we cannot claim the circuit is “preserved.” If the neurons cannot fire or maintain a resting membrane potential, we haven’t preserved a brain; we’ve preserved a very complex sculpture.

To check the effectiveness of their protocols (That surprisingly often still operate by manipulating the ratios of the 4 horseman: DMSO, EG, PG and sucrose/trehalose), most groups default to immunofluorescence, cell counts, or Western blots because they are cheap, fast, and operationally simple. A full round of IF or a Western blot costs well under $50–$150 per sample in consumables, requires only a microscope or a gel rig that every lab already owns, and can be completed within a day. These assays scale easily and fit into the workflow of junior technicians.

Functional assays, in contrast, are not prohibitively expensive, but they do require different infrastructure, expertise, and time. Of course, they are tissue-specific, but some examples include:

• Enzyme activity assays:
  Many kits run $3–20 per reaction;
  even kinetic assays on plate readers cost less than an antibody.

• Live-cell imaging of calcium flux, membrane potential, or synaptic activity:
  Dyes are $5–10 per sample,
  time on a decent confocal ~$20–80/hr internal recharge rate.

Out of assays that require a one time big investment but then serve for years:

• Mitochondrial respiration (Seahorse XF):
  Approx. $45–70 per well for sensor cartridges + plates;
  initial instrument cost $60–130k, so I get that some labs might not have it
  runtime ~2–3 hours.
  Once the instrument exists, per-sample costs are comparable to a good antibody.

• Electrophysiology (patch-clamp, MEA):
  Big up-front cost ($40–150k),
  but per-sample consumables are low (~$5–15).
  The true cost is expertise and labor, not materials.

• Flow cytometry (functional reporter dyes):
  Per-sample consumables $2–6 per sample for live-cell functional dyes (calcium flux, ROS, mitochondrial potential, apoptosis), plus basic tubes and buffers.
  The initial instrument cost is high ($80–350k, depending on configuration), so not every lab owns one directly, but almost all institutions have a shared core facility.

These were for cells. For organs it goes without saying that the ultimate success test is transplantation.

In other words, the barrier is not money, it’s culture and convenience (and the specialized trainee to run eg patch clamping, but that is case-specific)
For most experiments, running a functional readout costs:

• 2–3× more per sample than a basic Western blot,

• but 10× more information about whether the cell actually works.

The difference between “cheap” and “functional” is typically a few dozen dollars per sample, not thousands (assuming the lab has access to equipment (or collaborators)). Cryopreservation research has historically chosen structural assays because they’re accessible and familiar, not because functional assays are financially out of reach.

Do you have any other '“cheap and easy but useful” functional assay examples?

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Why Validation Matters On Many Levels

True functional validation must happen across every layer of biological organization:

• Cellular Level: Cellular “viability” assays like Trypan Blue exclusion, Calcein-AM or DAPI staining set an exceptionally low bar. They report membrane integrity or general reductive activity, but say little about whether the cell can perform the function it is biologically designed for (and are so easy to misinterpret depending on what resolution you set, or which counting paramters you use). Across cell types, cryopreservation routinely preserves morphology and markers while degrading performance. Cardiomyocytes may remain viable yet lose contractility or exhibit abnormal excitation–contraction coupling. Immune cells frequently maintain surface markers and transcriptomes but show reduced proliferation, cytokine release, phagocytosis, migration, or cytotoxicity. Neural cells can look morphologically intact yet lose calcium synchrony, axonal transport efficiency, neurotransmission fidelity, or spontaneous electrophysiological activity.

  The implication is straightforward: meaningful post-thaw assessment must evaluate contractility, metabolic flux, chemotaxis, electrophysiology, enzyme kinetics, or calcium signaling, not simply membrane integrity or marker expression.

• Organ Level: At the organ scale, functional validation is non-negotiable because structure and physiology frequently diverge in meaningful ways after cryopreservation or traditional preservation methods. Simply observing intact vasculature or acceptable histology does not guarantee an organ will perform its biological functions once rewarmed or reperfused.

  For instance, normothermic machine perfusion (NMP) has emerged clinically because static cold storage alone often fails to sustain metabolic and functional integrity in donor organs. NMP enables ongoing metabolism and direct functional evaluation including oxygen consumption, lactate clearance, bile production, and urine output during ex vivo perfusion, and these metrics correlate more strongly with graft viability than histology alone. This phenomenon has been repeatedly documented across organs such as liver and kidney grafts subjected to NMP prior to transplantation.

  In kidney transplantation research, ex vivo perfusion parameters such as creatinine clearance, arterial flow patterns, and oxygen consumption during normothermic perfusion have been used to distinguish functional from non-functional grafts, even when biopsy histology shows comparable architecture. A detailed cryopreservation study of vitrified kidneys (Han et al., 2023 - if you are still not familiar with it, shame on you;)) further demonstrates this point empirically: histology and ultrastructure appeared near-normal, yet functional recovery measured by urine production, venous and urine electrolyte composition, and metabolic activity during NMP was essential to establish true viability. After transplantation into nephrectomized recipients, these functional measures normalized over time despite only focal histological injury, underlining the fact that morphology alone cannot predict systemic performance.

  Similarly, in liver preservation, clinical and preclinical data show that dynamic perfusion metrics such as lactate clearance, bile output, and ATP content during NMP are far more predictive of transplantability than static histological assessments. Whereas static cold preservation may maintain gross structure, it often permits metabolic deterioration and ischemia–reperfusion injury that only becomes evident through dynamic function testing.

  Even outside strict cryopreservation work, transplantation research emphasizes that functional testing on machine perfusion platforms, measuring vascular resistance, metabolic waste clearance, oxygen extraction, and organ-specific secretory function, outperforms histology and conventional viability staining in predicting outcomes. This reflects a broader consensus in the field that structure is a necessary but insufficient indicator of biological utility.

The Path Forward: Standardization

If we want cryopreservation to be a scalable pillar of regenerative medicine, we need a “Functional Registry.” We must move beyond “post-thaw recovery” percentages and toward standardized benchmarks:

1. If you insist on cell research, do at least a metabolic flux analysis: Metabolic flux analysis is the most universally informative functional metric for cryopreserved cells, because energy metabolism is the earliest and most sensitive point of failure. However, it should be treated as a baseline assay rather than the definitive functional test, since optimal readouts are cell-type–specific (e.g., electrophysiology for neurons, contractility for cardiomyocytes, cytotoxicity for immune cells).

2. Integrated “Omics”: A persistent limitation in cryopreservation research is the near-total absence of post-thaw multi-omics profiling. When a functional assay under-performs, each omics layer supplies a distinct forensic tool:

   • Transcriptomics immediately flags whether the problem is upstream at the gene-expression level: it reveals stress-induced transcriptional programs (e.g., massive upregulation of HSPA1A, ATF4, or CHOP), repression of lineage-specific or functional genes (e.g., downregulation of INS, PDX1, or MYH6), or aberrant activation of apoptosis/senescence modules. If the cells look alive but do not function, transcriptomics tells you the blueprint itself is corrupted.

   • Proteomics localizes damage one layer downstream: it quantifies actual protein abundance, post-translational modifications, misfolding (increased ubiquitinated or carbonylated proteins), chaperone overload (elevated HSP70/90), or proteolytic degradation (cleaved caspases, proteasome subunits). It can show that even though the mRNA for a critical enzyme or channel is present, the functional protein is missing, aggregated, or inactivated—explaining why the functional test collapsed.

   • Metabolomics (and lipidomics) exposes the final functional bottleneck: it detects ATP/ADP collapse, accumulation of reactive oxygen species markers (8-OHdG, 4-HNE), depleted glycolytic or TCA-cycle intermediates, membrane lipid peroxidation, or toxic cryoprotectant metabolites. These profiles reveal whether the cell has entered a metabolically crippled state even though transcription and translation initially occurred—directly accounting for loss of contractility, secretion, or motility in the functional assay.

   Through integrating these readouts, researchers can now answer the precise question “why did the functional test fail?” with mechanistic insights: transcriptional repression, protein-level damage, or metabolic collapse. This granularity transforms cryopreservation optimization from trial-and-error into targeted engineering of the exact step that broke.

3. In Vivo Transplantation: The ultimate functional test: can a preserved tissue integrate and sustain life in a model organism? It can also apply to organoids (see my latest post for examples)

Why This Matters More Than Ever

1. Reproducibility and Scalability: Cryoexperiments are expensive and technically demanding. If protocols are validated only on viability, labs waste years chasing artifacts. Rigorous functional benchmarks let us compare protocols apples-to-apples and accelerate iteration.

2. Regulatory and Clinical Reality: Regulators (FDA, EMA) demand potency assays for advanced therapy medicinal products (ATMPs). Viability alone won’t cut it for organ banking or future cryonics-derived regenerative therapies.

3. AI Scaling: At the intersection of AI and cryopreservation, functional data is gold. Based on the results of multiple functional assays, AI can predict optimal vitrification cocktails, cooling and warming protocols, and foundational models simulate rewarming damage. But the training data must be functional metrics, not just survival. Garbage viability data in, garbage predictions out.
   

TL;DR
Don’t publish a cryo study without functional validation.

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Most cell cryopreservation is routine. Whole-organ vitrification has taken major steps forward in rats and even toward liter-scale CPA volumes (I talk about it in the last post). Organoids sit in an awkward middle ground: too large and structured to behave like simple cell suspensions, too small and avascular to benefit from classic organ perfusion strategies. So where are we really, in 2025–2026, with organoid cryopreservation?

What has actually been cryopreserved and functionally revived?

Intestinal organoids ✅

Human intestinal and colonic organoids can be frozen, thawed, and expanded with preserved stemness and the ability to regenerate epithelium-only enteroids/colonoids. Detailed protocols describe dissociating organoids from matrix, resuspending them in DMSO-containing freezing media, long-term storage in liquid nitrogen, and subsequent thawing that yields viable cultures capable of multiple passages and differentiation. Even biopsy specimens can be cryopreserved and later used to generate new GI epithelium-only organoids, which is crucial for biobanking patient material. However, the biopsy specimens are cut into tissue chunks, and cryopreserved via slow freezing in ready-made, DMSO-based cryomedia, so, although very useful, it’s not a breakthrough for cryobiology. Same for the intestinal organoids which are first centrifuged and then treated like normal cells would be.
Another study developed a protocol for mouse colon organoids, supported by theoretical modeling of heat and mass transfer. That study preserved the entire organoid on a Matrigel AND (!) transplanted the thawed organoids into mouse colon to confirm regenerative capacity, which is a bigger step for cryobiology.

Brain organoids ✅

You’d be surprised to know that there is a lot of progress in brain organoid cryopreservation! In one of my favorite papers in cryo ever, Xue et al. (2024) preserved large, multilayered human brain organoids without destroying their architecture or neural identity. They generated cortical organoids from H9 human embryonic stem cells and allowed them to mature to day 21–28, at which point they contain ventricular-zone-like radial structures, proliferative Sox2⁺ neural progenitors, differentiated MAP2⁺ neurons, and early network activity. Crucially, the authors cryopreserved intact whole organoids, not dissociated clusters or centrifuged pellets, selecting spheres of comparable size before freezing to avoid size-dependent variability. Organoids were immersed directly into cryopreservation medium composed of methylcellulose, 10% ethylene glycol, 10% DMSO, and the ROCK inhibitor Y-27632 (they called this cocktail “MEDY”) and then frozen using a controlled cooling protocol. No pelleting step was used, and no mechanical disruption occurred before or after freezing; the entire structure was thawed intact, transferred back into culture, and evaluated as a single unit. The strength of the study lies in how comprehensively they quantified post-thaw recovery. First, morphological integrity was strikingly well preserved: organoids maintained their ventricular-zone-like architecture and layered cortical organization, something the field had previously failed to achieve. The MEDY organoids did not fragment, swell abnormally, or collapse into debris (common outcome under DMSO-only conditions, which produced large amounts of cell debris and even complete dissociation in the sucrose groups). Quantitatively, MEDY-treated organoids showed high retention of Sox2⁺ progenitors and MAP2⁺ neurons, each >1.5-fold higher than in DMSO-only controls, and apoptotic cells were minimal, in stark contrast to trehalose-, sucrose-, glucose-, and proline-supplemented media, which produced extensive cell death. Functionally, the thawed organoids recovered robust neurite extension when embedded in Matrigel: axonal projections in the methylcellulose–ethylene glycol conditions (the core of the MEDY formulation) were significantly longer than those preserved with DMSO alone, demonstrating that not only cell survival but neuronal outgrowth capacity was maintained. The MEDY protocol scaled beyond a single organoid type, successfully preserving dorsal forebrain, ventral forebrain, optic vesicle, spinal cord, and even epilepsy patient-derived organoids without architectural collapse or loss of regional identity. The next step for future studies would be to functionally test them.

Heart organoids ✅
Do you recall nanowarming with iron oxide particles from my last post? It turns out this technique enabled cardiac organoid cryopreservation! The development of a heart organoid vitrification workflow coupled to Fe₃O₄-based magnetic nanowarming, enabled rapid, spatially uniform rewarming of vitrified cardiac organoids. In this system, post-thaw heart organoids show significantly improved survival, beating rate, contractility, histological integrity, and multi-electrode array readouts compared with conventional slow-warming approaches, suggesting that nano-rewarming can mitigate thermal stress and ice-related damage in larger 3D cardiac constructs.

Lung, Liver and pancreatic organoids 🫤
I have not found papers that cover whole liver organoid cryopreseration, but there has been a paper that successfully cryopreserved and later cultured, smaller chunks of the liver organoid. For lungs and pancreatic islets, I only found papers that describe cryopreserving cells, and growing an organoid from thawed cells.

Kidney Organoids ✅
Human kidney organoids derived from iPSCs or primary tissue can now be reliably cryopreserved as intact whole structures. A 2024 vitrification protocol achieved ~91% post-thaw viability, preserved nephron segments (podocytes and tubules), and retained regenerative capacity against toxins like cisplatin comparable to fresh controls.

Did I miss any organoids you found interesting in terms of cryo? Let me know in the comments:

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What is the next frontier?

The first frontier is functionally validated preservation. Many protocols define “success” as post-thaw morphology plus a viability stain. That may be adequate for routine passaging, but it is not enough for organoids used as quasi-clinical surrogates. The second frontier is controlled CPA delivery and removal. The main technical bottleneck is still how to load enough cryoprotectant to avoid ice, without inflicting lethal osmotic stress or toxicity. The third frontier is volumetric nanowarming at organoid scale. Nanowarming has already demonstrated major advantages over convective rewarming in perfused rat hearts and large CPA volumes: faster, more uniform heating and dramatically reduced risk of devitrification.Finally, there is a conceptual frontier: standardization and biobanking. Right now, every lab has its own slightly modified “house protocol.” As organoids move toward clinical and regulatory environments, we will need harmonized, validated cryopreservation workflows that define acceptable viability thresholds, functional readouts, and molecular fidelity benchmarks.

How to get to the next frontier of organoid cryopreservation?

The review paper by Han et al (2024) from Dr Yi Xu’s lab where I have the honor of practicing at, outlines the roadmap for organoid cryopreservation that extends beyond saying “better CPAs, less thermal gradients”. That paper makes it clear that the future of organoid cryopreservation depends on technologies that solve the physical constraints of 3D tissues. Microfluidics is one of the most transformative directions: instead of dunking organoids into high-dose vitrification solutions, microfluidic platforms allow precise, model-based CPA loading, using controlled flow, stepwise concentration ramps, and real-time osmotic tuning to avoid the catastrophic swelling and shrinkage that occur in bulk methods. These chips also let researchers measure permeability parameters directly in organoids, giving the field its first chance to design CPA schedules based on kinetics rather than guesswork. On the vitrification side, the review emphasizes “minimal-volume” formats such as Cryomesh, Cryotop, and hollow fibers, all of which achieve faster cooling and warming by physically reducing the thermal mass around each organoid. A Cryomesh, for example, spreads organoids across a thermally conductive lattice that wicks away heat during plunging, while ultrathin films on Cryotop devices allow vitrification using only microliters of solution meaning higher cooling/warming rates without raising CPA concentration.

For short-term storage, the paper highlights technologies that avoid freezing entirely. Oil-sealed supercooling keeps organoids in a metastable, ice-free state by physically isolating the medium from air, preventing heterogeneous nucleation and allowing storage at −4 to −20 °C without vitrification. Isochoric supercooling takes the idea further: by sealing samples in a rigid, constant-volume chamber, any attempt at ice formation immediately raises pressure, suppressing further crystallization. This allows low-CPA or CPA-free preservation with surprisingly high functional recovery in tissues like islets and engineered cardiac constructs.

Have you heard of any of these technologies? Let me know in the comments!

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Why does organoid cryopreservation matter?

If you are like me your initial reaction to this substack would be “okay, okay, cool, but let’s move to organs, or anything that brings us closer to the whole-organism cryo”. However, just like it was shown in the Han et al (2024) review, organoids can be used as a testing ground not only for drug discovery, but also for novel cryotech, giving more reliable and scalable results than cell cultures.

For drug discovery and toxicology, cryopreserved organoid banks would allow standardized, repeatable assays across batches, sites, and years. For personalized medicine, the ability to freeze and share patient-derived organoids would underpin multicenter trials where different interventions are tested on genetically matched tissue. For regenerative medicine, cryopreservation is the only way to decouple the timing of tissue manufacture from the timing of clinical need, especially for pancreatic, hepatic, and cardiac constructs destined for transplantation. So if you are not convinced that the cool cryotech will storm from organoid cryo research, at least be certain that there is a lot of capital that can be activated for organoid banking.

There’s also a deeper continuity here. The same problems we are solving for organoids (CPA toxicity, ice avoidance, thermal stress, nanowarming) are exactly the ones limiting whole-organ cryopreservation and long-term organ banking. Techniques developed for organoids will feed back into organ work, and vice versa. In that sense, every incremental improvement in organoid cryopreservation is a step toward a future where storing complex human tissues, on demand and at scale, is normal rather than aspirational.

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I feel like the world of cryopreservation is getting more and more buzz lately, but the state of the art still remains the 2023 rat kidney successful cryopreservation, validated by transplantation. Has the needle moved forward at all recently? I analyzed the google scholar profiles of the most impactful PIs in cryo, and then did a more general key word search in the attempt to answer this question. Here is my subjective take on the three most impactful recent publications in cryobiology.

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1) Scaling Vitrification to Larger Organs

Gangwar, L. et al. (2025). “Physical vitrification and nanowarming at liter-scale CPA volumes: toward organ cryopreservation”
Nature Communications: https://www.nature.com/articles/s41467-025-63483-2

This paper will likely be cited as the 2025 cryopreservation publication.

What they did:
The authors developed a protocol to take multi-liter volumes of cryoprotectants (CPAs), big enough for human organs, and vitrify them without ice. They combined controlled cooling with nanowarming (using iron oxide nanoparticles activated by magnetic fields) for fast, uniform reheating. They also vitrified porcine livers without ice formation, but did not rewarm them for this study.

Why it matters:
So although this is just a proof of concept for bags of CPAs, rather than actual organs, this study addresses two of the hardest problems in large-scale cryopreservation:

1. Avoiding heterogeneous ice formation during cooling, and

2. Preventing cracks and devitrification during warming.

This work demonstrated avoidance of the former in pig livers, and latter with the liter volume CPAs.

Impact:
For the first time, organ-sized vitrification seems engineerable. This is the clearest line of sight for organ cryobanking there’s ever been. And although the largest successfully rewarmed organ, validated by transplantation, remains the rat kidney (also by Bischof group), this paper sends the message “we are going after human organ cryobanking”, which is a big step for academia-based cryo.

Other fun facts from the paper:

I really liked the figures where they approximate the necessary cooling and warming rates for selected organs, as a function of their adult-size-volume. It shows that the minimum cooling rate decreases with volume, which is not intuitive. Let’s talk a little bit more science. What the model is really capturing is geometry and thermal diffusion. Larger organs have a larger characteristic length scale (Lc)​, which fundamentally changes how heat is transported to the center. The center becomes the bottleneck. Once the surface vitrifies and thermal gradients establish, the minimum rate required to avoid ice nucleation at the center is governed by bulk heat transport, not just surface kinetics.

Panel (b) is even more interesting to me.

The blue curve shows how the minimum cooling rate collapses rapidly as Lc​ increases. For small characteristic lengths (sub-centimeter), the required cooling rates are extremely high. But as you move toward organ-scale dimensions, the required rate approaches very low values. At the same time, the red curve shows the tradeoff: as Lc​ increases, the minimum vitrifiable CPA concentration increases. So while the cooling constraint relaxes, the chemical toxicity and vascular damage due to viscous liquid perfusion constraints tighten. That tradeoff is the real engineering battlefield.

Did you think I’d stop with the science talk so soon? You must not read enough of my posts;)

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The actual fun is with the figure about nanowarming. First: nanowarming is fundamentally different from conductive warming.

In traditional warming, heat diffuses from the surface inward: Bigger organ → longer diffusion path → slower center warming. That produces smooth scaling behavior. Nanowarming does not rely primarily on surface heat flux. Instead, iron oxide nanoparticles distributed through the vasculature absorb energy from an alternating magnetic field and generate heat volumetrically. The heating rate depends on:

• Nanoparticle concentration

• Magnetic field strength and frequency

• Distribution uniformity

• Vascular volume fraction

• Local perfusion accessibility

• Thermal conductivity of tissue + CPA

That already tells us it won’t scale cleanly with organ volume.

This paper shows that nanowarming rate correlates with vascular fraction, not volume. Organs with higher vascular density (lung, eye) show higher predicted nanowarming rates. Organs with lower vascular fraction (ovary, testis) show lower rates even if their volumes are comparable or larger. So the dominant scaling variable here is not size, but how well you can perfuse nanoparticles into the tissue. You cannot assume constant nanoparticle concentration across organs. Perfusion resistance, capillary density, endothelial permeability, and vascular geometry differ significantly.

On the note of nanowarming, another 2025 paper that deserves a shoutout is “Scalable Purification of Iron Oxide Nanoparticles for Organ Cryopreservation and Transplantation” also from the Bischof group. I’m placing it as a sub-mention, because although it didn’t show us a new proof of concept, it’s crucial for the field because it gives an exact recipe for the nanoparticles that I described above. The group could have as well formed a company around it and cash the ready-made product. I highly recommend everyone in the field to read it and understand it, for higher-order ideation on the new cryo solutions.

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2) Functional Revival of the Mouse Hippocampus Cells After Whole-Brain Vitrification

Preprint: “Functional recovery of the adult murine hippocampus after cryopreservation by vitrification”
bioRxiv, https://www.biorxiv.org/content/10.1101/2025.01.22.634384v3

This preprint matters, because instead of just survival (the days of which as a valid cryo endpoint for cells are largely over) it shows function.

What they showed:
The part of the paper that is the most exciting for me shows that they cryopreserved the entire mouse brain, and although the whole organ was clearly damaged, the hippocampus, or at least the cells extracted from it, show electrochemical functionality. The whole brain was clearly stressed. There were perfusion challenges, dehydration issues, variability in recovery rates, and a non-trivial failure fraction.

Why it matters:
This is not a “perfect organ recovery” story, but it’s the largest, partially successful, published attempt at brain cryopreservation.

3) Increased understanding of organ cracking - and how it can be prevented

Paper: Higher Glass Transition Temperatures Reduce Thermal Stress Cracking in Aqueous Solutions Relevant to Cryopreservation
Scientific Reports - https://www.nature.com/articles/s41598-025-13295-7

Problem:

One of the major problems in organ cryopreservation is that they tend to crack during warming. Cooling and warming generate temperature gradients, which produce tensile stress in brittle aqueous glasses. Moreover, almost all CPA cocktails have a narrow glass transition temperature (Tg) band (≈ −120 to −130 °C), and Tg itself has rarely been treated as a controllable mechanical variable.

This paper asks what if fracture risk is fundamentally tied to Tg?

What they did:

The authors vitrified and rewarmed separate DMSO, glycerol, xylitol, and sucrose solutions directly imaging how much cracking occurred. Importantly, they differ in their Tg by more than 50 °C (concentration-dependent). They then built a mechanical model to calculate how much tensile stress develops during cooling for solutions with different Tg values. Both the experiments and the simulations showed the same result: solutions with higher glass transition temperatures cracked less and experienced lower peak tensile stress during cooling. In the simulations, lowering Tg increased the maximum stress by roughly fourfold across the range studied

Why it matters

This paper suggests that the dominant CPA chemistries may be thermomechanically suboptimal. Although they allow us to vitrify large samples, their Tg makes them prone to stress accumulation. This work reframes Tg as a design variable in next-generation CPAs.

Looking Forward

We’re still early in the timeline from proof-of-principle to clinical utility for organ cryobanking. Let alone revival of the whole organism. Major hurdles remain:

• Full organ post-thaw functionality (especially vascular integrity)

• Standardized CPA formulations with minimal toxicity

• Integrated warming methods compatible with clinical workflows

But the research published in 2025 shows those hurdles are ripe for engineering and scientific attack, and that practical cryopreservation is transitioning from science fiction to scientific reality.

Did I miss any of the papers you found impactful? Are you looking for answers for specific cryo questions? Let me know in the comments!

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Is it not a massive milestone that we can now handle the entire ordering process through an LLM? Think about it, it’s not just about food! You tell the AI your symptoms, and it selects and sends the right medication straight to your door (for the non-emergency stuff, obviously). That is a fundamental shift in how we live.

I was so pumped that I decided to write this article, which, for the record, is my first piece that has absolutely nothing to do with longevity or cryo.

While researching, I discovered that Google actually launched a similar capability a few weeks ago called the Universal Commerce Protocol (UCP). But why hasn’t anyone heard about it? It barely made a ripple in the West. Alibaba, on the other hand, didn’t just wait for people to get excited. They noticed the lack of enthusiasm and leaned in hard spending 3 billion RMB on “free delivery coupons.”

The result? Qwen is now the most downloaded AI app in China. It turns out that when you bridge the gap between “cool tech” and “free lunch” people finally pay attention (and the boba economy spiked - people placed over 10 million orders in 9 hours, surging to 120 million in 6 days)

I decided to compare Google and Alibaba on their AI e-commerce startegy. Why not other companies? For e-commerce discussion, payment is a key discriminator. In the west, out of the 4 LLMs that matter (ChatGPT, Grok, Gemini and Claude), only Google has payment infrastructure (Google pay). In China, Alibaba and Tencent control the dominant payment rails, but only Alibaba aligns its LLM, commerce platform, delivery network, and Alipay into a single vertically integrated transaction stack.

Let’s try to understand what made it possible for Alibaba to such severly outcompete Google with basically the same e-commerce concept. It boils down to 4 categories: the LLM itself, shopping platform, payment and delivery.

Layer 1: The Intelligence Layer

At its core, the intelligence layer is about the raw capabilities of the AI models powering these systems: Alibaba’s Qwen versus Google’s Gemini. Both are cutting-edge LLMs, but their strengths diverge in ways that reflect their ecosystems and target markets.

Gemini shines in global multimodality with seamless integration. It’s ranked highest on benchmarks like MMMU-Pro (multimodal understanding) and Video-MMMU, making it ideal for diverse, international applications where users might upload photos of ingredients for recipe suggestions or analyze videos for shopping recommendations. This broad capability stems from Google’s vast data resources, including YouTube and Search, allowing Gemini to process real-world inputs in a more “global” way. For instance, in agentic commerce, where AI acts on user intent, like booking or buying Gemini excels in long-horizon, multi-step workflows, such as planning a trip that involves parsing flight images, audio reviews, and code for integrations.

Qwen, on the other hand, is finely tuned for Chinese agentic tasks, emphasizing efficiency in multi-step reasoning and tool coordination within Alibaba’s closed ecosystem. It’s optimized for high-context scenarios common in China, like coordinating with local services (e.g., Ele.me for food, Amap for navigation). Benchmarks show Qwen3-Max-Thinking edging out Gemini 3 Pro on rigorous tests like Humanity’s Last Exam, highlighting its prowess in complex, agentic workflows requiring external data retrieval. Qwen’s hybrid reasoning supports custom agents for domain-specific tasks, such as e-commerce customization, without rigid structures.

But here’s the crux: Intelligence alone is inert without action. In China, Qwen wields “execution authority” through Alibaba’s vertical stack directly interfacing with Taobao, Ele.me, and Alipay to fulfill orders autonomously. Tell Qwen to “order a customized boba,” and it searches inventory, applies tweaks, processes payment, and dispatches a rider, all without leaving the chat.

In the West, Gemini operates in a fragmented landscape. Google’s UCP is an open standard, relying on partnerships with Shopify for e-commerce, Uber Eats for delivery, Stripe or PayPal for payments, and others. This means Gemini must negotiate permissions at every step: API calls to check stock, user consents for data sharing, compliance with local regulators (e.g., GDPR in Europe), and navigation through competing ecosystems like Apple Pay or Amazon. Fragmentation introduces latency and potential failures if a partner app glitches. As one analysis notes, while Gemini offers higher autonomy in reasoning, its agentic tasks often require more user guidance due to these external dependencies. The result? Agentic commerce feels constrained, like a powerful engine throttled by red tape. To truly compete, Google might need deeper integrations or acquisitions, but antitrust scrutiny could hinder that.

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Layer 2: Commerce Density

China’s setup is a perfect storm for agentic AI: extreme urban density, scooter-based logistics, designated delivery cabinets, and the majority of households relying for delivery for everyday meals.

Average delivery times hover around 20-30 minutes, with costs per order low (around 18% of total payment, often subsidized). Abundant riders (estmiantes say about 10 million via platforms like Ele.me and Meituan combined). With China’s food delivery market at $40.2 billion in 2024, and 545 million users placing orders frequently, the ecosystem thrives on scale. We are moving from “Why would I take a 10 minute walk to a nearby shopping complex for a boba, if I can order it online?” to “Why would I bother opening an app and choosing the restaurant, and my order if I can just ask Qwen to do it for me while I take a bath/play my game/ work on my project*?”

Contrast this with the US: Suburban sprawl dominates, where homes are spread out, requiring car-based logistics that inflate costs (25% of order value) and times (often 45-60 minutes). Higher labor costs mean fewer riders per capita, and without widespread smart lockers, deliveries involve more handoffs. Consumers pay 30-40% more than the base food price via apps like DoorDash or Uber Eats, making it feel premium rather than routine. Usage reflects this: Americans order delivery about 4.5 times per month on average, versus China’s near-daily habit for many. App-switching friction compounds it; Gemini might suggest a meal, but you bounce to Uber Eats for checkout, killing the seamless agentic flow.

Also let’s not forget that Qwen food delivery is a huge win for people like me who take an hour to decide what do eat: “is it healthy?”, “but I had Thai yesterday…”, “I don’t feel like having chicken tonight”… Now, I can talk about it with AI and it can even suggest what would be healthier for me given my past food order history and biormakers (if I upload them;))

Layer 3: Payment

Alipay, launched by Alibaba in 2004, dominates China’s mobile payments landscape with over 1.43 billion users worldwide as of mid-2024, capturing around 54% of the third-party mobile payment market alongside WeChat Pay’s 40%. This duopoly accounts for over 94% of transactions, fueled by seamless QR code and biometric (face ID or PIN) payments that eliminate app-switching (try paying with cash in China, and DM me with how it went;)). In Qwen’s agentic setup, users confirm orders conversationally, and Alipay handles the rest—applying discounts, processing via stored credentials, and completing in seconds without leaving the chat. Low fees (often 0.1 yuan for small transfers) and no interest on wallets keep funds circulating within the ecosystem, boosting retention.

In Google’s UCP, payments integrate with Google Pay, using saved Wallet credentials for quick checkouts in AI Mode on Search and Gemini, with PayPal support incoming. However, this federated model introduces friction: reliance on third-party processors like Stripe or PayPal means variable fees (2-4% vs. China’s near-zero for in-ecosystem transfers), potential API latencies, and compliance with diverse regulations (e.g., GDPR, PCI DSS). Adoption lags, only about 25% of Americans use mobile wallets like Google Pay, compared to China’s 73%+ for daily transactions. Cultural factors compound this: U.S. consumers prefer credit cards for rewards and protections, leading to slower shifts from traditional methods.

What’s next?

Naturally, right after the initial wonder of my first LLM purchase, I started having questions and concerns. Thankfully, it’s still a human-in-the-loop system, so AI can’t just go rogue and buy stuff with your money that it deems beneficial. The next big worry? Ads. If the cognitive load of switching platforms and fumbling through payments gets wiped out, you could just tap an ad and buy on impulse, especially when it’s hyper-targeted, with the AI knowing your emotions, health status, and financial situation. Any illusion of independent thinking while shopping? Trashed. Also, will this further exacerbate the problems baked into the platform economy, if your shop (at least in China) isn’t hooked into delivery networks, you basically don’t exist (though the case is nuanced, ofc). These AIs train on skewed data, potentially funneling you toward Alibaba-favored brands or culturally dominant options, quietly marginalizing less tech oriented sellers (this tips hard into our Right to Be Remembered paper).

And then there is a case of privacy. Qwen already taps into my order history and could soon pull biomarkers or mood data from wearables, handing Alibaba (or hackers) a god’s-eye view of my life.

There are questions, there are simulations, there is a ton of scenarious.

But for now… hey Qwen, can you get me a big cup of the duck poop hand beaten lemon ice tea, no sugar, less ice?

iykyk

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Gleb first contacted me after I published my piece on cryo-mummies. His work sounded familiar; he extracted proteomic signatures from mammoth remains preserved in permafrost. However, when he mentioned he “also ~revived~ count Dracula” I raised my eyebrow enough to dare ask what he meant. It turns out that Gleb and his team can detect proteomic signatures from any “super old” object, and the insights could help us verify historians’ claims about the past. However, Gleb quickly realized that the tech he developped can be applied not only to study the past, but also predict the future.

The Past

In biophysics, there’s a concept known as the folding funnel; it’s a “path” proteins follow as they fold into their functional shapes. But what happens to these shapes over decades, centuries, or even tens of thousands of years? Using paleontological and archaeological objects ranging from insects trapped in amber to parchment manuscripts and even seeds that sprouted after 30,000 years in Siberian ice (yes, they s p r o u t e d = were functionally reviewed) they’re mapping how the tertiary structure of proteins evolves with time. To determine that, Gleb’s team uses the patented EVA-chip extraction system: a deceptively simple strip that functions like a molecular sponge. Originally designed for proteomics and metabolomics, EVA technology allows researchers to gently lift proteins, metabolites, and even viral components from delicate surfaces like 300-year-old parchment, frescoes, or biological remains without destroying the sample. It’s precise enough to distinguish high- from low-abundance proteins, yet flexible enough to work across disciplines, from oncology biopsies to pigment analysis in medieval wood paintings or even Leonardo da Vinci’s Donna Nuda, where it uncovered egg-based binders and restoration layers. Most importantly, the researchers can distinguish the “real marks” from modern contamination picked up on the strip, mainly by assessing how old the molecules are via oxidation, racemization or deamidation. By fractionating molecules based on charge and hydrophobicity, EVA strips enable non-destructive, high-resolution sampling, offering a viable path forward for both preserving the past and diagnosing the present. In fact, because the samples remain stable at room temperature, this technology may one day be embedded into wearable health sensors passively collecting molecular snapshots as you go about your day (see later in the article in “the future” paragraph). However, staying within the historical realm, recent applications include Dead Sea Scrolls fragments revealing scribes’ plant-based diets via legume peptides, and the Aleppo Codex’s fungal culprits behind its corrosion, demonstrating EVA’s power to rewrite history one molecule at a time.

My two favorite of Gleb’s team findings include:

● Bulgakov’s Manuscript Findings: Historically exciting discoveries emerged from the examination of the margins on Mikhail Bulgakov’s Master and Margarita manuscript (one of my favorite novels!) , shedding light on his deteriorating health and reliance on pain-relieving drugs during his final creative years.The non-invasive EVA analysis of the 1930s–1940s typescript pages detected elevated periostin, N-acetyl-β-glucosaminidase and nephrin, peptides (a hallmark of advanced kidney disease) corroborating historical accounts of Bulgakov’s nephrosclerosis, which plagued him in his last four years. Even more poignantly, morphine metabolites were identified in sweat residues, indicating the author’s self-administration of the opioid as a palliative for excruciating renal pain, a detail that humanizes the tormented genius behind his satirical masterpiece (and maybe explains a lot of the scenes…)

● Milan’s Lazaretto Death Registries Findings: Likewise, revelations came from deeper probes into the death ledgers preserved in Milan’s lazaretto amid the devastating 1630 plague epidemic, uncovering traces of the era’s microbial horrors and human desperation. Applied to the yellowed, ink-stained parchments recording over 15,000 plague fatalities, the EVA strips revealed Yersinia pestis antigens (the bubonic plague pathogen) and Bacillus anthracis spores (anthrax), confirming infectious agents lingered on the documents themselves likely from contaminated hands or air. Human traces painted a grim tableau: mouse proteins in scribe sweat suggested famine-forced cannibalism on rodents for sustenance, while cereal and legume peptides hinted at meager diets; heavy metals like lead and copper from inks, plus stress-induced cortisol markers, underscored the scribes’ exhaustion and peril as they toiled in the plague-ravaged quarantine zone

But Gleb didn’t stop at deciphering history. In one of his most audacious experiments, he placed a single protein between superconducting electrodes to create a Josephson junction, a quantum device more commonly used to detect exotic electronic behaviors in physics labs. By inserting a biological molecule into this setup, his team demonstrated that proteins can function not just as static samples but as active elements in quantum sensing platforms. Why does this matter? Because the Josephson junction allows researchers to measure submolecular electrical properties like polarizability, magnetic susceptibility, and electron density without destroying the molecule. In simple terms, this gives us a non-invasive way to peer into the 3D architecture and behavior of individual proteins, something that traditional tools like crystallography or mass spectrometry often struggle to do at such sensitivity or in near-physiological conditions.

At first glance, studying a single protein might sound like an academic exercise; after all, what could one molecule possibly reveal? Traditional techniques require millions of identical proteins, harsh preparation steps, or freeze-frame snapshots that miss dynamic behavior. In contrast, this quantum approach allows scientists to observe how a single, intact protein behaves in real time; how it folds, misfolds, or responds to external stimuli like heat, pH shifts, or even a drug molecule. It matters because biology is full of rare, unstable, or mutated protein forms that escape bulk analysis but drive devastating diseases. With a setup like this, we could detect the earliest signs of molecular dysfunction.

The Future

After years of tracing how proteins persist through millennia, Gleb asked a natural question: what if we turned these tools forward onto living people? He founded Spectrophon Ltd. in 2012, building continuous monitors that offer underexplored capabilities such as the Dehydration Body Monitor (DBM) for real-time sweat and electrolyte tracking during exercise, a non-invasive glucose sensor for diabetes care, troponin detection for early cardiac events, luteinizing hormone for ovulation, and even external toxins like PM2.5. Validated in clinical trials, like a 2017 study of 200 participants showing high accuracy in hydration metrics via Samsung-integrated wearables, these devices apply EVA-inspired molecular capture to everyday life, turning smartphones into proactive health guardians.

Recently, Gleb’s team extended their work into orbit; collaborating with NASA-affiliated researchers to explore how minimally invasive wearables could monitor astronauts’ physiological responses to extreme space stressors like cosmic radiation and microgravity. Using EVA-based biosensing platforms and surface-friendly extraction films, they aim to passively collect biomarkers from sweat, skin, or interstitial fluid during spaceflight. These collaborations are now helping to evaluate markers like cortisol, cardiac stress indicators, dehydration status, and even brain injury biomarkers (like those relevant to traumatic brain injury) using non-invasive dermal interfaces.

Take home message

Zilberstein’s EVA threads remind us that we’re all archives in motion. Whether decoding the fevered scrawls of a plague-ridden scribe or alerting you to a stealthy arrhythmia mid-hike, this molecular bridge reanimates the human story, urging us to live not in isolation, but as echoes of the vast, unfolding now. Gleb’s company is open to partnerships, of any nature: wearable, history decoding, smart sensors - you name it!

Our molecular marks will outlast us.

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Over the weekend, I found myself right in the heart of the World Laureates Association gathering in Shanghai. The conference center was filled with some of the most celebrated minds in science: Nobel, Turing, Breakthrough Prize winners, you name it. I listened to their talks, asked questions, broke bread (well, rather bao buns) with them, listening to their stories, searching for stories I can’t find on wikipedia. And out of that slightly chaotic bundle of conversations, a few insights started to stand out to me about where the real challenges and opportunities in science are right now. Plus, of course, a bit of life advice sprinkled in.

The State of Curiosity

There were multiple, parallel sessions going on, my attention was brough to the one was what I called “academic speed dating”: five-minute “flash pitches” by “young scientist” (quotation marks because they were all associate professors at top iniversities) followed by rapid-fire questioning from laureates. It was chaotic in the best possible way. Physicists interrogated bioengineers, chemists poked at astrophysicists, and somehow it all made sense. A reminder that innovation often happens in collisions, not committees.The talks themselves felt like previews of a near future already in beta: a biodegradable pacemaker smaller than a rice grain, light-powered enzymes disassembling plastics at the molecular level, graphene nanofluidics that probably defy intuition but definitely got everyone nodding wisely.

After the “speed dating” all laurates at the session had a panel disussion. “Blue-sky research” was the quiet hero of the event. I was not familiar with the term they all advocated for so intensly; it’s research with no immediate application, just audacity. The Chan Zuckerberg Foundation seems to be betting big on it, and the laureates were eager to follow.

And here’s another little gem I hadn’t really considered before: intellectual property. It turns out that at places like Stanford, your IP is fully yours, which was kind of a revelation to me. I hadn’t really thought much about who owns the ideas you come up with in academia until this conversation. It definitely made me realize that the whole intellectual property landscape is a bigger deal than I gave it credit for, and it’s something I’ll be paying a lot more attention to from now on.

The Machines and the Minds

My favorite track was ofcouse the AI and supercomputers one. It ranged from scientific foundations for quantum computing to thinking ahead of the risks and premises how the world might change. Laureates have a way of slipping existential bombs into casual talk. One suggested that universities might lose relevance within five years, as AI outpaces academic infrastructure and learning becomes distributed, automated, decoupled from institutional calendars. He also pointed out that we’re publishing way too many papers, and that flood of publications can give the public a really skewed idea of what scientists actually do. I agree with this one; sometimes the publications I see really belong to Substack more than to a journal. So in a world when a growing number of papers, especially the non-experimental ones, are written by LLMs, reviewed by LLMs, and submitted by humans who pretend this is not the case, can we honestly say each of the is adding to the understanding of the world? I am not arguing against the AI use, on the contrary, but I do think that a new benchmarking system for “scientific novelty and applicability” is needed.

That thought carried into a discussion about AI’s own limitations. Large models have already consumed most written text, so their future depends on learning efficiency rather than volume. Energy costs, adaptability, and self-supervised learning came up repeatedly, plus the question of whether AGI might appear faster than regulation can spell it.

Meanwhile, the physicists turned the conversation toward supercomputers and the arms race of computation. The unit inherent to supercomputer’s power is an exaflop: 10^18 calculations per second. If every person on Earth did one calculation every second, it would take more than 4 years to do what an exascale computer can do in just one second. What can you actually do with that kind of power? Well, it opens up incredible possibilities. Exascale computing can be used for things like simulating complex climate models, running highly detailed genomic analyses, designing new materials at the atomic level, or even modeling the entire human brain in ways we couldn’t before. The discussions highlighted four key directions. First, there’s quantum metrology (measuring stuff, units etc) , which leverages the delicate properties of quantum states to measure tiny effects with a precision that classical methods just can’t match. Then there’s quantum communication, which is all about securely sharing quantum bits between partners using keys that can’t be eavesdropped on. We also touched on quantum simulation, where we mimic complex materials or exotic quantum phases by using systems of artificial atoms. And finally, of course, there’s quantum computing itself, harnessing superposition and entanglement to solve certain problems that are just out of reach for classical computers. There’s still plenty of research ahead before these technologies are fully realized, but these are the big directions that are shaping the field right now.

So, talking about the top supercomputers, the current top five systems are a pretty impressive lineup. You’ve got El Capitan, Aurora, and Eagle, all American systems. Then there’s Jupiter, which is German, and finally one from Italy, which I did not expect. There’s also one up in Finland. But what really caught my attention was that China was not on the leaders board; it turns out that China has stopped submitting performance data to the global repository that tracks the fastest supercomputers. So while we have this sense that they’re likely outperforming almost everyone else at scale, we just don’t have the actual numbers to confirm it.

The Human Element

After a few hours of exaflops, quantum roadmaps, and politely phrased existential dread, the conversations drifted back to a simpler variable: attention. Several laureates admitted their most durable work began in their twenties or thirties, because reputation hadn’t yet crowded out curiosity and there was still enough ignorance to try the impolite experiments. The warning was implicit (protect your attention before committees rent it by the hour), as was the reassurance (early sparks survive if you feed them consistently, not theatrically).

I also had the heart to heart conversation with one of the laureates about the quality of human relationships. I was shocked when he mentioned working on your shadown side, because I though it was just a gen-alpha tiktok trend, but it turns out that it is deeply rooted in Jungien psychology. He fiercly claimed that we are unable to be flly at piece and we will always be ruled by our emotions, if we don’t identify, reason though and see the impact of our childhood traumas. A discount code to betterhelp, anyone?

The most unexpectedly personal moment, however, came when I introduced myself as Polish. People genuinely praised my country’s scientific and democratic transformation in the recent years. Growing up, I was told I had two obstacles: being a woman and being from Poland. Sitting there among laureates who saw neither as disqualifiers, I realized one of those barriers had quietly dissolved.

If the weekend had a moral, it was this: the tools are getting sharper, AI, quantum, exascale, but the real differentiator remains the same. It’s the willingness to ask naïve questions in sophisticated rooms.

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This raises a provocative question: if we analyze which proteins survived and which degraded in naturally frozen mummies, do we gain insights relevant to modern cryopreservation science?

🔴 TRIGGER WARNING: I included the photo of Ötzi at the end of the article

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“Hey Professor, we found a cryo-mummy” - what do you do?

Maixner et al.’s team must have been pretty shocked when they heard about Ötzi; it was an opportunity that they for sure have not anticipated to ever stumble upon. So, in such an unprecedented scenario, what did they do? First, they had to figure out what to look for. DNA could reveal where he came from and what traits he carried, but to understand what was happening in his body at the time of death, they needed to study the proteins. The team set out to reconstruct the proteome (the complete set of detectable proteins from the Iceman’s brain) to see if any molecular traces of stress or injury had survived.

But before they could extract anything, they had to decide where to sample. Earlier CT scans had shown a that only the occipital lobe of the brain (“vision region”) was relatively well preserved. Guided by CT imaging and 3D navigation, the researchers performed a precise endoscopic procedure to collect two tiny, rice-grain-sized, biopsies from this region. Because the tissue had been desiccated for more than five millennia, it was first rehydrated using saline to allow ancient proteins to dissolve again, and then treated with a solvent that breaks open cell membranes and unfolds proteins without destroying them, particularly effective for lipid-rich neural material. Two complementary extraction protocols were used: one gentle, targeting soluble proteins, and one harsher, involving longer sonication cycles to release material still bound within the debris. The final step was liquid chromatography–mass spectrometry (LC–MS) which eventually revealed over 500 proteins, including neuronal cytoskeletal proteins (neurofilament light and medium chains), synaptic vesicle proteins (synapsins), and glial fibrillary acidic protein (GFAP). These findings confirm that not only connective tissue but actual neuronal and glial structures persisted after 5,000 years.

The types and properties of the proteins that remained

So, what kind of proteins actually made it through five millennia of freezing, drying, and slow decay? And do they have anything in common like structure or function that makes them tougher than others?

The survivors tend to be structural and extracellular proteins. Collagens (yes, the ones from your longevity powders), for example, have rope-like triple-helix structure, reinforced by special chemical bonds, giving them exceptional resistance to breakdown. Keratins, the proteins that form hair and skin, also endure thanks to tight internal bridges that protect them from oxidation and water damage. In the Iceman’s case, researchers also found blood-clotting and wound-related proteins, such as fibrin and fibronectin, in the region of the brain where CT scans had shown trauma. These proteins naturally form dense networks when blood coagulates, which may have helped them resist enzymatic decay. Small fragments of hemoglobin, trapped within the remains of red blood cells, also survived, protected by the cell’s lipid envelope and the stabilizing iron in the heme group. Another group of persistent molecules were glycoproteins decorated with sugar chains, or N-linked glycans. These sugars act like natural armor, shielding the underlying protein from chemical attack. Similar protective effects likely explain why immune proteins such as complement fragments and serpins have also been detected in other mummified tissues as their modular, compact shapes make them unusually stable.

By contrast, proteins that are flexible or metabolically active in life like enzymes or membrane-bound transporters were almost completely gone. These molecules rely on fluid, dynamic shapes that collapse once the cell dies and its lipid membranes disintegrate.

In short, the molecular survivors of deep time are those built for strength, not speed; proteins meant to provide scaffolding, protection, or repair, persisted.

Here is a quick table for comparison:

Structural Lessons

The Iceman’s proteome reinforces a key principle of cryopreservation: stability isn’t just about temperature, it’s about molecular architecture. What survived did so through dense crosslinking, restricted mobility, and built-in redundancy; what didn’t were molecules that relied on flexibility and fluidity for function.For cryobiology, that distinction is crucial. The same forces that destroyed Ötzi’s enzymes and membranes like dehydration, oxidation, and local pH shifts also threaten modern tissues during freezing and thawing. The lesson is that preservation must be structural as well as thermal. If we want to safeguard living systems, we need strategies that reinforce the vulnerable domains of proteins like stabilizing active sites, shielding flexible loops, and preventing lipid peroxidation before cooling ever begins.

The challenge for cryobiology is to reverse-engineer those outcomes deliberately: to design environments where even the dynamic and fragile parts of life can withstand the long pause, and still remember how to move when warmth returns.

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Physiology or Medicine : Peripheral Immune Tolerance, senescent T cells and sterile inflammation

Mary E. Brunkow, Fred Ramsdell, and Shimon Sakaguchi received the 2025 Nobel Prize in Physiology or Medicine “for their discoveries concerning peripheral immune tolerance.” In simple terms, their work explained how the immune system learns to avoid attacking its own body. More specifically, they identified the transcription factor FOXP3 as the master regulator of CD4⁺ FOXP3⁺ regulatory T cells (Tregs) which are specialized cells that suppress autoreactive T cells in peripheral tissues to maintain self-tolerance and prevent autoimmunity

Does this discovery apply to geroscience? Absolutely, though the connection lies more with the T cells than peripheral immunity. As we grow older, Tregs become numerically and functionally compromised, and senescent. This dysregulation leads to excessive secretion of pro-inflammatory cytokines such as IL-6 and TNF-α, accelerating stem-cell exhaustion, tissue degeneration, and metabolic dysfunction. One of the most discussed phenomena in aging biology today is “inflammaging”, which is the chronic, low-grade inflammation that gradually escalates with age. The problem is so fundamental that chronic inflammation is now recognized as one of the 12 updated Hallmarks of Aging. There are many promising interventions to reduce the inflammation, but to stay within the realm of T cells and geroscience, it is worth noting that CAR-T cells are explored as potential senolytic agents. Chimeric Antigen Receptor (CAR) T cells are patient-derived T cells modified to recognize specific surface antigens. In oncology, they destroy malignant cells; in aging research, early preclinical work now retools them to identify and eliminate senescent cells expressing markers like uPAR or B2M. Conceptually, this represents the inverse of Treg biology: while Tregs suppress excessive immune attack, CAR T cells can be programmed to selectively remove chronically harmful or senescent targets. Both rely on deep understanding of T cell signaling and specificity fields that trace their mechanistic roots directly back to FOXP3 and the regulatory circuitry uncovered by the 2025 Nobel laureates.

Now, does the 2025 Nobel prize in medicine apply at all to cryopreservation? I thought I would be writing a fully speculative paragraph here, but surprisingly, the relationship between T cells and cryopreservation was explored before. To get the obvious out of the way, T cells are preserved in the lab setting to be further used for experiments, and CAR-T cells are cryopreserved as ready-made therapy to be shipped to patients. However, since T cells rely on their ability to detect antigens on the surface of other molecules, their structure responsible for detection must be preserved intact so that the cells could regain function. In spleen samples as well as in CART precursor cells, it was found that while viability decreased after cryopreservation, the functionality remained high. Scaling up, in cryopreserved thymus slices transplantation experiments, the organ was able to regain T cell differentiating ability. I have not found papers exploring what happens to Tregs during whole organ cryopreservation, but a very interesting and applicable insight can be borrowed from the field of transplantology. A concept crucial to avoid in organ cryopreservation is ischemia (when an organ or parts of it don’t get enough blood and oxygen). A study of livers procured for transplant found that ischemic injury, which can happen when you perfuse the organ, attracts a CD4+ helper t cells, which initiate a cascade of inflammatory response. Although this process was not studied under cryopreservation conditions, it is likely that the same scenario happens. Perhaps, including anti-inflammatory small molecules targeting TNF-α or IL-6, or the damage associated molecular patterns introduced by the paper, into the cryoprotective cocktail would improve the perfusion outcomes? If you were looking for a project idea, you just found one.

Chemistry: Metal–Organic Frameworks, bone scaffolds and oocytes

Susumu Kitagawa, Richard Robson, and Omar Yaghi were awarded the Nobel Prize in Chemistry “for the development of metal–organic frameworks (MOFs).” The term MOF refers to a class of crystalline, porous coordination polymers in which metal ions or clusters (the “nodes”) are connected by organic linkers (the “bridges”) to form extended, three-dimensional networks with internal cavities and channels. These structures combine high surface area, tunable pore size and chemistry, and modular functionalization.

Beyond gas capture and catalysis (their most mature applications), MOFs are increasingly leveraged in biomedical engineering and drug delivery. Their porosity and internal cavities allow for high loading of therapeutic molecules, while the ability to modify pore environments, surface chemistry, and degradation rates enables precise control of adsorption and release kinetics, organ targeting, and stimuli responsiveness (pH, redox, temperature). This great review describes how MOF platforms have been used to deliver small-molecule drugs, nucleic acids, imaging agents, and combination therapeutics, often improving solubility, bioavailability, and localization.

MOFs have already been studied in the context of aging and bone regeneration. Scientists in Shanghai created magnesium and cerium-based metal–organic frameworks (Ce-MOFs) and implanted them onto aged mouse femurs with bone defects to test whether they could rejuvenate old bone tissue. These Ce-MOFs acted like long-lasting antioxidants as the cerium ions could switch between Ce³⁺ and Ce⁴⁺ states to keep removing reactive oxygen species (ROS). This reduced oxidative stress and inflammation, both of which normally drive bone cell aging. As a result, bone marrow stem cells in the treated mice stayed healthier and more active, and immune cells shifted toward a tissue-healingtype . In the end, imaging and histology showed that the treated bones had more new bone growth and stronger structure, suggesting that Ce-MOFs can help restore the regenerative capacity of aging bone.

Now, for cryopreservation, I envision MOFs great future. Several applications of MOF to cryopreservations have already been published. My favorite one is iron-based amino-functionalized metal–organic frameworks (Fe-MOFs) to improve oocyte cryopreservation. The method suppressed ice crystal growth to just 16.8% of the size formed in pure water by forming hydrogen bonds through their amino and carboxyl groups, which allowed them to adsorb onto and stabilize the ice–water interface. Remarkably, these Fe-MOFs also showed intrinsic photothermal activity, rapidly heating from 25 °C to over 86 °C under near-infrared light enabling fast, uniform rewarming that prevents recrystallization. When used to vitrify mouse oocytes, this MOF achieved 95.1% post-thaw survival, even when traditional cryoprotectant concentration was half of what is recommended in the standard procedures. The rewarmed oocytes then have undergone normal fertilization and embryonic development.

In another attempt, researchers in South Korea designed zirconium-based metal–organic frameworks (MOF-801) as smart antifreeze particles to protect cells during freezing. They shaped these nanoparticles with precise surface curvature and attached amino acids valine and threonine, which are the same ones that natural antifreeze proteins use. This gave the MOFs a surface pattern that could “fit” onto the edges of forming ice crystals, blocking them from growing into sharp, cell-damaging structures. When used to freeze human kidney epithelial cells, the smallest MOFs kept more than 60% of the cells alive after thawing (compared to 40% control), showing that engineered materials could physically control how ice forms

On a more speculative note, the blood–brain barrier (BBB) represents a crucial challenge in cryonics. Some cryoprotectants are unable to penetrate it effectively, while in other cases, excessive permeability can lead to cerebral edema. Although this cool paper does not address cryonics directly, the section on ischemic stroke (ischemic injury) demonstrates how metal–organic frameworks can be engineered to deliver drugs across the BBB. Could similar strategies be adapted for cryoprotectant delivery in cryonics applications? Finally, if MOFs can combine mass transfer modulation, structural stability, and heating response, they would transform cryoprotectant design from a passive solvent problem to an active scaffold problem.

In summary, MOFs bring architectural precision to processes that have traditionally been chemically chaotic.

Physics: tunneling, quantum computers and liquid helium

The 2025 Nobel Prize in Physics was awarded for showing that quantum effects can appear in large-scale electrical circuits. The scientists, John Clarke, Michel Devoret, and John Martinis, used a special kind of metal called a superconductor, a material that, when cooled to just a few degrees above absolute zero, can carry electricity with no resistance at all. In this ultra-cold state, they placed a tiny barrier inside a superconducting loop and discovered that electrons could tunnel through the barrier (think of a baseball passing through a wall but the wall is intact, in one piece), a purely quantum behavior where particles pass through obstacles they normally couldn’t.

This showed that even a visible, man-made circuit can behave like a quantum system if it’s cold enough. The same tunneling effect that allowed current to jump between energy levels became the basis for superconducting qubits, where scientists now use microwave pulses to control those quantum jumps encoding information in states that can exist as 0, 1, or both simultaneously until measured. This discovery made it possible to build quantum computers and opened an entirely new chapter in how we understand and manipulate matter under extreme cold.

Here, the connection to aging or cryo will be even more stretched than before, but indeed, there are some, like the fact that supercomputers might be able to figure out both;) Although there are no practically useful quantum computers yet, there are quantum-classical generative algorithms that already contribute to science, such as finding the small molecules targeting the KRAS proto-onco gene. I talk about it in my paper Deep learning and generative artificial intelligence in aging research and healthy longevity medicine which has an entire part on quantum computing and aging.

In cryo, the most direct parallel to superconductivity is temperature control. While superconductors operate near –273.15°C (absolute zero), cryopreservation typically cools tissues only to –196°C which is the temperature of liquid nitrogen, at which biological time effectively stops, eliminating the need to go colder for preservation purposes. To reach –273°C, physicists use dilution refrigerators that first pre-cool with liquid helium-4 to about 4 K, then rely on the phase separation of helium-3 and helium-4 isotopes to absorb heat through evaporative cooling inside multi-stage, vibration-isolated vacuum systems designed to maintain stable quantum states. Intriguingly, liquid helium has also been explored as a potential cryogenic medium for biology, offering ultra-rapid cooling rates that enhance vitrification, the glass-like solidification without ice crystal formation, in sensitive cells such as human stem cells, bovine oocytes, and HeLa or L929 cell lines. However, helium’s cost and scarcity have so far prevented large-scale use in organ preservation.

Literature - the appocalypse approaches - so what?

László Krasznahorkai’s Literature Nobel celebrates an author whose works explore persistence amid decay. I admit that I have not read his books yet (in my Audible queue!), but I watched a summary video of his writing to prepare myself for writing this paragraph- there is a lot of talk about death. His meditations on entropy, continuity and the fear of the apocalypse resonate with the existential dimensions of longevity science and moral grounds of cryonics. I prepared a few quotes from his books:

“Death, he felt, was only a kind of warning rather than a desperate and permanent end.”

This line could easily appear in a cryonics manifesto or an essay on digital immortality (uploading). In both, death is not the end but a threshold, an interruption before a new continuity; you would have to first cease to exist in the current world, but would (assuming that the tech works) reappear in either the completely different world with possibilities unlimited by the biological constraints (uploading) or in the world that is (hopefully) more technologically, medically and society advanced than what you left behind (cryonics). While the author has most likely meant eternal life in some sort of a religious understanding, if we are being really honest with ourselves, each of the three options (“heaven”, cryonics, uploading) relies on hope of revival in a better place. It is not the purpose of this substack to convince you to believe in an, but please, do me a favor and entertain the idea that the scientifically grounded life extension operates on almost the same moral ground as any religion. In that sense, scientifically grounded life extension is not a rebellion against religion but its secular translation: a faith that technology, not divinity, may one day redeem the finite.

The quote below operates on the same interpretation as the one above, but I am inserting it here for you to get to know László Krasznahorkai’s signature style - loooong sentences.

“I would leave everything here: the valleys, the hills, the paths, and the jaybirds from the gardens, I would leave here the petcocks and the padres, heaven and earth, spring and fall, I would leave here the exit routes, the evenings in the kitchen, the last amorous gaze, and all of the city-bound directions that make you shudder, I would leave here the thick twilight falling upon the land, gravity, hope, enchantment, and tranquility, I would leave here those beloved and those close to me, everything that touched me, everything that shocked me, fascinated and uplifted me, I would leave here the noble, the benevolent, the pleasant, and the demonically beautiful, I would leave here the budding sprout, every birth and existence, I would leave here incantation, enigma, distances, inexhaustibility, and the intoxication of eternity; for here I would leave this earth and these stars, because I would take nothing with me from here, because I’ve looked into what’s coming, and I don’t need anything from here.”

Heaven, cryonics, or uploading… all three emerge from the same existential grammar. They are variations of one sentence humanity keeps rewriting: that decay may not be destiny. Krasznahorkai writes it in prose; scientists write it in protocol.

Peace prize: you can’t push the needle of science forward if you are too conncerned with surviving until the next day

The 2025 Nobel Peace Prize was awarded to María Corina Machado, the Venezuelan opposition leader, for her unwavering fight to restore democracy through nonviolent means. The Nobel Committee recognized her for showing exceptional courage in resisting authoritarian rule, uniting the opposition, and advocating for peaceful political transition despite personal risk. Although the Peace Prize is definitely the hardest to tie to longevity and cryopreservation directly, we have to agree that the questions about life extension as a science can only be asked either in times of prosperity or by people with enough financial and contextual stability to ponder such a high risk ground. Political stability and ethical governance are prerequisites for advancing and democratizing life-extending and biopreservation technologies. Cryonics and longevity medicine cannot flourish in environments of distrust, censorship, or inequity; they rely on transparency, regulation, and moral legitimacy.

Economics: understand why things work, and keep on innovating

The 2025 Nobel Prize in Economic Sciences was awarded to Joel Mokyr, Philippe Aghion, and Peter Howitt for explaining why economic growth can persist instead of reaching a natural limit. Mokyr traced this shift to the Enlightenment, when technological progress became anchored in scientific reasoning; people no longer just used inventions but sought to understand why they worked, enabling cumulative innovation. Aghion and Howitt formalized this process through the theory of “creative destruction,” in which new technologies continuously replace old ones. Their work showed that progress depends on allowing renewal while managing the disruption it brings. The main lesson for science here is simple: never rely 100% on dogma. I am not suggesting that we question everything as constant skepticism would paralyze progress, but if your findings do not immediately align with what is known or hypothesized, or if your peers dismiss your idea, it is worth giving it focused time, because there may be potential in it. Think about the relatively recent amyloid hypothesis scandal: for decades, the scientific community accepted amyloid buildup as the obvious driver of Alzheimer’s disease, but later it turned out that some of the foundational data supporting that view had been fabricated.

Another takeaway from the 2025 Economics Nobel is the importance of understanding why things work, not just that they work. For example, we know that cryoprotectants function at the physical level to prevent ice formation, but we still do not fully understand the molecular basis of their toxicity. Better insight into what actually happens during cryoprotection could lay the groundwork for designing new, less toxic cryoprotectants directly echoing Mokyr’s reasoning that progress accelerates when mechanisms are understood, not merely applied. To connect Aghion and Howitt’s “creative destruction” to longevity science, consider the evolution of biological aging clocks, where new algorithms continuously replace older ones. Each refinement in geroprotector design or cryoprotectant chemistry mirrors the economic cycle of innovation and obsolescence: hypotheses are tested, fail, and are replaced by better ones. Sustained progress, whether in economies or in biomedicine, requires openness to revision, tolerance for failure, and the belief that improvement has no final state. The Nobel’s message, stripped of discipline, is simple: growth, like life, persists only when we keep dismantling what once seemed sufficient.

Quick summary to shine in conversations

Now, if you want to use this substack as a conference networking conversation driver (or if you are a “fun fact!” A person like me;)) here is a quick summary table.

Do you want to bet on when and to whom the first Nobel prize on aging or cryo is going to be awarded? Comment and let’s discuss